add static dataset and prompts

.gitattributes

@@ -57,3 +57,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+static_evaluation_set/v0_09-01-25/extension/causal_arc_extension.json filter=lfs diff=lfs merge=lfs -text
+static_evaluation_set/v0_09-01-25/logical/causal_arc_logical.json filter=lfs diff=lfs merge=lfs -text

prompts/program_synthesis/program_synthesis_nexamples4_prompts.json

@@ -0,0 +1,66 @@
+{
+    "SCMm5ob": {
+        "L1": {
+            "Replicate 0": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 8, 0, 0, 0, 0, 7, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 8, 0, 0, 0, 0, 0, 0, 0, 2], [7, 7, 0, 7, 0, 0, 0, 2, 0, 0], [8, 0, 0, 0, 0, 0, 8, 0, 0, 0], [0, 8, 0, 0, 3, 0, 0, 0, 0, 3], [0, 0, 0, 0, 0, 0, 0, 0, 2, 0], [0, 0, 0, 3, 7, 0, 0, 0, 0, 8], [0, 0, 0, 3, 0, 0, 0, 2, 0, 0], [2, 0, 2, 7, 3, 8, 0, 0, 0, 0]] -> [[0, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 2, 0, 0, 0, 0, 0, 3, 0], [0, 0, 3, 0, 8, 0, 7, 0, 0, 0], [8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 0, 3, 0, 0, 7, 0, 0, 0], [2, 0, 0, 0, 2, 7, 3, 0, 0, 0], [0, 0, 0, 2, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 7, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2]] -> [[0, 0, 2, 0], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\n",
+            "Replicate 1": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 3, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 7, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 3, 0, 0, 0, 0], [0, 0, 3, 0, 0, 8, 0, 0, 0, 2], [3, 0, 0, 0, 0, 0, 3, 3, 0, 0], [0, 0, 0, 0, 0, 3, 2, 0, 0, 0], [0, 0, 8, 0, 2, 8, 3, 3, 0, 0], [7, 0, 0, 8, 0, 2, 2, 0, 0, 0], [0, 0, 8, 0, 3, 7, 7, 7, 0, 0]] -> [[0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 8, 0, 0, 0, 0, 7, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 8, 0, 0, 0, 0, 0, 0, 0, 2], [7, 7, 0, 7, 0, 0, 0, 2, 0, 0], [8, 0, 0, 0, 0, 0, 8, 0, 0, 0], [0, 8, 0, 0, 3, 0, 0, 0, 0, 3], [0, 0, 0, 0, 0, 0, 0, 0, 2, 0], [0, 0, 0, 3, 7, 0, 0, 0, 0, 8], [0, 0, 0, 3, 0, 0, 0, 2, 0, 0], [2, 0, 2, 7, 3, 8, 0, 0, 0, 0]] -> [[0, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\n",
+            "Replicate 2": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 3, 8, 7], [0, 0, 2, 0, 0, 0, 0, 0, 8, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3], [2, 0, 0, 0, 0, 0, 0, 0, 8, 0], [0, 0, 3, 0, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 0, 3, 8, 8, 0], [0, 0, 0, 0, 0, 0, 8, 8, 0, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 3, 2, 0, 0, 0, 0, 7, 0]] -> [[0, 8, 0, 0], [0, 8, 0, 3], [0, 8, 0, 3], [7, 8, 0, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 2, 0, 0, 0, 0, 0, 3, 0], [0, 0, 3, 0, 8, 0, 7, 0, 0, 0], [8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 0, 3, 0, 0, 7, 0, 0, 0], [2, 0, 0, 0, 2, 7, 3, 0, 0, 0], [0, 0, 0, 2, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 7, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2]] -> [[0, 0, 2, 0], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 0, 3, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 2, 3, 0, 0, 0], [7, 0, 0, 0, 3, 0, 7, 0, 0, 0], [0, 0, 0, 0, 2, 0, 7, 0, 0, 0], [7, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 7, 8, 8], [0, 7, 3, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 0], [7, 8, 0, 0], [7, 8, 0, 3], [7, 8, 0, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\n",
+            "Replicate 3": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 2, 0, 0, 0, 0, 0, 3, 0], [0, 0, 3, 0, 8, 0, 7, 0, 0, 0], [8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 0, 3, 0, 0, 7, 0, 0, 0], [2, 0, 0, 0, 2, 7, 3, 0, 0, 0], [0, 0, 0, 2, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 7, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2]] -> [[0, 0, 2, 0], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 8, 2, 0, 0], [0, 0, 0, 0, 0, 0, 7, 7, 0, 0], [0, 0, 0, 2, 8, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 2, 0], [7, 8, 0, 0, 7, 0, 0, 0, 0, 3], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [0, 0, 0, 0, 0, 0, 0, 2, 0, 0], [0, 0, 0, 7, 0, 0, 0, 0, 0, 0], [0, 2, 8, 0, 2, 0, 0, 3, 8, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 7]] -> [[0, 0, 2, 0], [0, 0, 2, 0], [0, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\n",
+            "Replicate 4": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 3, 8, 7], [0, 0, 2, 0, 0, 0, 0, 0, 8, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3], [2, 0, 0, 0, 0, 0, 0, 0, 8, 0], [0, 0, 3, 0, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 0, 3, 8, 8, 0], [0, 0, 0, 0, 0, 0, 8, 8, 0, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 3, 2, 0, 0, 0, 0, 7, 0]] -> [[0, 8, 0, 0], [0, 8, 0, 3], [0, 8, 0, 3], [7, 8, 0, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 3, 8, 7], [0, 0, 2, 0, 0, 0, 0, 0, 8, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3], [2, 0, 0, 0, 0, 0, 0, 0, 8, 0], [0, 0, 3, 0, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 0, 3, 8, 8, 0], [0, 0, 0, 0, 0, 0, 8, 8, 0, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 3, 2, 0, 0, 0, 0, 7, 0]] -> [[0, 8, 0, 0], [0, 8, 0, 3], [0, 8, 0, 3], [7, 8, 0, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 8, 0, 0, 0, 0, 7, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 8, 0, 0, 0, 0, 0, 0, 0, 2], [7, 7, 0, 7, 0, 0, 0, 2, 0, 0], [8, 0, 0, 0, 0, 0, 8, 0, 0, 0], [0, 8, 0, 0, 3, 0, 0, 0, 0, 3], [0, 0, 0, 0, 0, 0, 0, 0, 2, 0], [0, 0, 0, 3, 7, 0, 0, 0, 0, 8], [0, 0, 0, 3, 0, 0, 0, 2, 0, 0], [2, 0, 2, 7, 3, 8, 0, 0, 0, 0]] -> [[0, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 3, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 7, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 3, 0, 0, 0, 0], [0, 0, 3, 0, 0, 8, 0, 0, 0, 2], [3, 0, 0, 0, 0, 0, 3, 3, 0, 0], [0, 0, 0, 0, 0, 3, 2, 0, 0, 0], [0, 0, 8, 0, 2, 8, 3, 3, 0, 0], [7, 0, 0, 8, 0, 2, 2, 0, 0, 0], [0, 0, 8, 0, 3, 7, 7, 7, 0, 0]] -> [[0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\n"
+        },
+        "L3": {
+            "Replicate 0": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 0, 0, 2, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 3, 0, 3, 0, 7], [0, 0, 0, 0, 0, 3, 2, 3, 2, 7], [0, 0, 0, 3, 8, 0, 3, 8, 2, 7], [0, 0, 0, 0, 0, 0, 0, 2, 0, 3], [0, 8, 0, 0, 0, 0, 0, 0, 8, 0], [3, 0, 0, 0, 3, 0, 0, 8, 0, 8], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 2, 0, 3, 0, 0, 7, 0]] -> [[0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 2, 0, 0, 0, 0, 0, 3, 0], [0, 0, 3, 0, 8, 0, 7, 0, 0, 0], [8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 0, 3, 0, 0, 7, 0, 0, 0], [2, 0, 0, 0, 2, 7, 3, 0, 0, 0], [0, 0, 0, 2, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 7, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2]] -> [[0, 0, 2, 0], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 3, 0, 7, 0, 0, 0, 3], [0, 0, 0, 2, 2, 0, 7, 0, 3, 0], [0, 2, 7, 0, 0, 0, 0, 2, 0, 0], [0, 0, 3, 0, 0, 0, 0, 3, 0, 3], [0, 7, 0, 0, 2, 0, 7, 7, 7, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 3, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 7, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 7, 2, 0, 0, 0, 0, 0, 0]] -> [[7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3]]\n",
+            "Replicate 1": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 3, 8, 7], [0, 0, 2, 0, 0, 0, 0, 0, 8, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3], [2, 0, 0, 0, 0, 0, 0, 0, 8, 0], [0, 0, 3, 0, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 0, 3, 8, 8, 0], [0, 0, 0, 0, 0, 0, 8, 8, 0, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 3, 2, 0, 0, 0, 0, 7, 0]] -> [[0, 8, 0, 0], [0, 8, 0, 3], [0, 8, 0, 3], [7, 8, 0, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[9, 9, 3, 9, 9, 9, 9, 9, 9, 9], [9, 9, 9, 8, 9, 9, 9, 7, 9, 9], [9, 9, 9, 9, 9, 9, 9, 9, 9, 9], [2, 9, 9, 9, 9, 3, 9, 9, 9, 9], [9, 9, 3, 9, 9, 8, 9, 9, 9, 2], [3, 9, 9, 9, 9, 9, 3, 3, 9, 9], [9, 9, 9, 9, 9, 3, 2, 9, 9, 9], [9, 9, 8, 9, 2, 8, 3, 3, 9, 9], [7, 9, 9, 8, 9, 2, 2, 9, 9, 9], [9, 9, 8, 9, 3, 7, 7, 7, 9, 9]] -> [[9, 9, 9, 3], [9, 9, 9, 3], [9, 9, 9, 3], [9, 9, 9, 3], [9, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 2, 0, 0, 0, 0, 0, 3, 0], [0, 0, 3, 0, 8, 0, 7, 0, 0, 0], [8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 0, 3, 0, 0, 7, 0, 0, 0], [2, 0, 0, 0, 2, 7, 3, 0, 0, 0], [0, 0, 0, 2, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 7, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2]] -> [[0, 0, 2, 0], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 3, 0, 7, 0, 0, 0, 3], [0, 0, 0, 0, 0, 0, 7, 0, 3, 0], [0, 0, 7, 0, 0, 8, 0, 0, 0, 0], [0, 0, 3, 0, 0, 0, 8, 3, 0, 3], [0, 7, 0, 0, 0, 0, 7, 7, 7, 0], [7, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 8, 0, 3, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 7, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 7, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 3], [7, 0, 0, 3], [7, 8, 0, 3], [7, 8, 0, 3], [7, 8, 0, 3], [7, 8, 0, 3], [7, 8, 0, 3]]\n",
+            "Replicate 2": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 3, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 7, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 3, 0, 0, 0, 0], [0, 0, 3, 0, 0, 8, 0, 0, 0, 2], [3, 0, 0, 0, 0, 0, 3, 3, 0, 0], [0, 0, 0, 0, 0, 3, 2, 0, 0, 0], [0, 0, 8, 0, 2, 8, 3, 3, 0, 0], [7, 0, 0, 8, 0, 2, 2, 0, 0, 0], [0, 0, 8, 0, 3, 7, 7, 7, 0, 0]] -> [[0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 8, 0, 3, 7, 7, 7, 0, 0], [7, 0, 0, 8, 0, 2, 2, 0, 0, 0], [0, 0, 8, 0, 2, 8, 3, 3, 0, 0], [0, 0, 0, 0, 0, 3, 2, 0, 0, 0], [3, 0, 0, 0, 0, 0, 3, 3, 0, 0], [0, 0, 3, 0, 0, 8, 0, 0, 0, 2], [2, 0, 0, 0, 0, 3, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 7, 0, 0], [0, 0, 3, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 7, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 2, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 2, 0, 0, 0, 0, 7, 3, 0], [0, 3, 7, 0, 0, 0, 2, 2, 0, 2], [7, 0, 0, 8, 2, 0, 0, 8, 8, 0], [7, 0, 0, 7, 7, 0, 0, 7, 0, 8], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 2, 0, 7, 0, 0, 8, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 2]] -> [[7, 0, 2, 0], [7, 0, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 0], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[9, 9, 9, 3, 9, 7, 9, 9, 9, 3], [9, 9, 9, 2, 2, 9, 7, 9, 3, 9], [9, 2, 7, 9, 9, 8, 9, 2, 9, 9], [9, 9, 3, 9, 9, 9, 8, 3, 9, 3], [9, 7, 9, 9, 2, 9, 7, 7, 7, 9], [7, 9, 9, 9, 9, 9, 9, 8, 9, 9], [9, 8, 9, 3, 9, 9, 9, 9, 9, 9], [9, 9, 8, 9, 9, 9, 9, 7, 9, 9], [9, 9, 9, 9, 9, 9, 9, 9, 9, 9], [9, 9, 7, 2, 9, 9, 9, 9, 9, 9]] -> [[7, 9, 9, 9], [7, 9, 9, 9], [7, 9, 9, 9], [7, 9, 9, 3], [7, 9, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\n",
+            "Replicate 3": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 0, 3, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 2, 3, 0, 0, 0], [7, 0, 0, 0, 3, 0, 7, 0, 0, 0], [0, 0, 0, 0, 2, 0, 7, 0, 0, 0], [7, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 7, 8, 8], [0, 7, 3, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 0], [7, 8, 0, 0], [7, 8, 0, 3], [7, 8, 0, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 8, 0, 3, 7, 7, 7, 0, 0], [7, 0, 0, 8, 0, 2, 2, 0, 0, 0], [0, 0, 8, 0, 2, 8, 3, 3, 0, 0], [0, 0, 0, 0, 0, 3, 2, 0, 0, 0], [3, 0, 0, 0, 0, 0, 3, 3, 0, 0], [0, 0, 3, 0, 0, 8, 0, 0, 0, 2], [2, 0, 0, 0, 0, 3, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 7, 0, 0], [0, 0, 3, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 3, 8, 7], [0, 0, 2, 0, 0, 0, 0, 0, 8, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3], [2, 0, 0, 0, 0, 0, 0, 0, 8, 0], [0, 0, 3, 0, 0, 0, 3, 0, 0, 0], [0, 0, 0, 0, 0, 0, 3, 8, 8, 0], [0, 0, 0, 0, 0, 0, 8, 8, 0, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 3, 2, 0, 0, 0, 0, 7, 0]] -> [[0, 8, 0, 0], [0, 8, 0, 3], [0, 8, 0, 3], [7, 8, 0, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 7, 2, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 7, 0, 0], [0, 8, 0, 3, 0, 0, 0, 0, 0, 0], [7, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 7, 0, 0, 2, 0, 7, 7, 7, 0], [0, 0, 3, 0, 0, 0, 8, 3, 0, 3], [0, 2, 7, 0, 0, 8, 0, 2, 0, 0], [0, 0, 0, 2, 2, 0, 7, 0, 3, 0], [0, 0, 0, 3, 0, 7, 0, 0, 0, 3]] -> [[7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 3], [7, 0, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\n",
+            "Replicate 4": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 0, 3, 0], [7, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 2, 3, 0, 0, 0], [7, 0, 0, 0, 3, 0, 7, 0, 0, 0], [0, 0, 0, 0, 2, 0, 7, 0, 0, 0], [7, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 7, 8, 8], [0, 7, 3, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 0, 0, 0], [7, 0, 0, 0], [7, 0, 0, 0], [7, 8, 0, 0], [7, 8, 0, 3], [7, 8, 0, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 0, 0, 2, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 3, 0, 3, 0, 7], [0, 0, 0, 0, 0, 3, 2, 3, 2, 7], [0, 0, 0, 3, 8, 0, 3, 8, 2, 7], [0, 0, 0, 0, 0, 0, 0, 2, 0, 3], [0, 8, 0, 0, 0, 0, 0, 0, 8, 0], [3, 0, 0, 0, 3, 0, 0, 8, 0, 8], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 2, 0, 3, 0, 0, 7, 0]] -> [[0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 0, 0, 3], [0, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [0, 0, 2, 0, 0, 0, 0, 0, 3, 0], [0, 0, 3, 0, 8, 0, 7, 0, 0, 0], [8, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 0, 3, 0, 0, 7, 0, 0, 0], [2, 0, 0, 0, 2, 7, 3, 0, 0, 0], [0, 0, 0, 2, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 7, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2]] -> [[0, 0, 2, 0], [7, 0, 2, 3], [7, 0, 2, 3], [7, 0, 2, 3], [7, 8, 2, 3], [7, 8, 2, 3]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 3, 0, 0, 0, 0, 0, 3], [0, 0, 0, 2, 2, 0, 0, 0, 3, 0], [0, 2, 0, 0, 0, 8, 0, 2, 0, 0], [0, 0, 3, 0, 0, 0, 8, 3, 0, 3], [0, 0, 0, 0, 2, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 8, 0, 0], [0, 8, 0, 3, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 2, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 3], [0, 0, 2, 3], [0, 8, 2, 3], [0, 8, 2, 3], [0, 8, 2, 3], [0, 8, 2, 3], [0, 8, 2, 3]]\n"
+        }
+    },
+    "SCMev5t": {
+        "L1": {
+            "Replicate 0": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 6, 6, 0, 0, 2, 2, 2, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 2, 2, 2, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 4, 4, 0, 0, 2, 2, 2, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[4, 0], [6, 0], [2, 2]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 2, 2, 0, 2, 2, 0], [0, 0, 0, 0, 2, 2, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 6, 6, 0, 0], [0, 0, 0, 0, 0, 6, 6, 6, 0, 0], [0, 4, 4, 4, 0, 6, 6, 6, 0, 0], [0, 4, 4, 4, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[4, 0], [6, 0], [2, 2]]\n",
+            "Replicate 1": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 0, 0, 0, 2, 2, 2, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 0, 0, 0, 2, 2, 2, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 6, 6, 0, 0], [0, 0, 0, 0, 0, 6, 6, 6, 0, 0], [0, 2, 2, 2, 0, 6, 6, 6, 0, 0], [0, 2, 2, 2, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 2, 2, 0, 2, 2, 0, 0, 0], [0, 0, 2, 2, 0, 2, 2, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 0, 0], [2, 2, 2]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 0, 0, 0, 2, 2, 2, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2, 0], [6, 6, 6]]\n",
+            "Replicate 2": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 6, 6, 0, 0, 2, 2, 2, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 2, 2, 2, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 4, 4, 0, 0, 2, 2, 2, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[4, 0], [6, 0], [2, 2]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 0, 0, 0, 2, 2, 2, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 6, 6, 0], [0, 4, 4, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0], [4, 4], [6, 6]]\n",
+            "Replicate 3": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 6, 6, 0, 0, 2, 2, 2, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 2, 2, 2, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 4, 4, 0, 0, 2, 2, 2, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[4, 0], [6, 0], [2, 2]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 2, 2, 0, 2, 2, 0], [0, 0, 0, 0, 2, 2, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 6, 6, 0, 0], [0, 0, 0, 0, 0, 6, 6, 6, 0, 0], [0, 4, 4, 4, 0, 6, 6, 6, 0, 0], [0, 4, 4, 4, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[4, 0], [6, 0], [2, 2]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 6, 6, 6, 0, 2, 2, 2, 0], [0, 0, 6, 6, 6, 0, 2, 2, 2, 0], [0, 0, 6, 6, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 2, 2, 0, 0], [0, 0, 0, 0, 0, 0, 2, 2, 0, 0], [0, 0, 6, 6, 0, 0, 2, 2, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2], [6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 6, 6, 0, 0], [0, 0, 0, 0, 0, 6, 6, 6, 0, 0], [0, 2, 2, 2, 0, 6, 6, 6, 0, 0], [0, 2, 2, 2, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 2, 2, 0, 2, 2, 0, 0, 0], [0, 0, 2, 2, 0, 2, 2, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 0, 0], [2, 2, 2]]\n",
+            "Replicate 4": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 6, 6, 6, 0, 2, 2, 2, 0], [0, 0, 6, 6, 6, 0, 2, 2, 2, 0], [0, 0, 6, 6, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 2, 2, 0, 0], [0, 0, 0, 0, 0, 0, 2, 2, 0, 0], [0, 0, 6, 6, 0, 0, 2, 2, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2], [6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 0, 0, 0, 2, 2, 2, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2, 0], [6, 6, 6]]\n"
+        },
+        "L3": {
+            "Replicate 0": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 6, 6, 0], [0, 4, 4, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0], [4, 4], [6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 6, 6]]\n",
+            "Replicate 1": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 6, 6, 0], [0, 4, 4, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0], [4, 4], [6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0], [0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 0, 0, 0, 2, 2, 2, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2, 0], [6, 6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 6, 6]]\n",
+            "Replicate 2": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 6, 6, 0], [0, 4, 4, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0], [4, 4], [6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0], [0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 6, 6, 0, 0, 2, 2, 2, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 2, 2, 2, 0, 0], [0, 0, 0, 0, 0, 2, 2, 2, 0, 0], [0, 4, 4, 0, 0, 2, 2, 2, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[4, 0], [6, 0], [2, 2]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 6, 6]]\n",
+            "Replicate 3": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 2, 2, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0], [6, 6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 6, 6, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 0, 0, 0], [0, 4, 4, 0, 0, 0, 0, 6, 6, 0], [0, 4, 4, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 6, 6, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 2, 2, 2, 0, 0, 4, 4, 4, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0], [4, 4], [6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 6, 6]]\n",
+            "Replicate 4": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 2, 2, 0, 2, 2, 2, 0, 0, 0], [0, 0, 0, 0, 2, 2, 2, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 6, 6, 6, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2, 0], [6, 6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by rotating or flipping it.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 0, 0, 0, 0, 0, 0], [0, 2, 2, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 6, 6, 0, 6, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0], [6, 6, 6]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 6, 6, 6, 0, 2, 2, 2, 0], [0, 0, 6, 6, 6, 0, 2, 2, 2, 0], [0, 0, 6, 6, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 2, 2, 0, 0], [0, 0, 0, 0, 0, 0, 2, 2, 0, 0], [0, 0, 6, 6, 0, 0, 2, 2, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 2], [6, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 6, 6, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 6, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[6, 6, 6]]\n"
+        }
+    },
+    "SCMfwpq": {
+        "L1": {
+            "Replicate 0": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [7, 6, 6, 0, 0, 0, 0, 0], [6, 0, 6, 0, 6, 0, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 4, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [7, 4, 4, 7, 7, 7, 7, 7], [6, 0, 6, 0, 6, 0, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 0, 0, 6, 6, 6, 0, 0], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 7, 4, 4, 4, 7, 7], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 6, 0, 0, 6, 0, 0], [6, 0, 0, 0, 6, 0, 6, 6], [0, 0, 0, 0, 0, 0, 0, 6], [0, 0, 0, 6, 0, 0, 0, 0], [7, 6, 0, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 6, 0], [6, 0, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 6, 6, 0, 6]] -> [[7, 7, 4, 7, 7, 4, 7, 7], [6, 0, 0, 0, 6, 0, 6, 6], [0, 0, 0, 0, 0, 0, 0, 6], [0, 0, 0, 6, 0, 0, 0, 0], [7, 4, 7, 4, 4, 7, 7, 7], [0, 6, 6, 0, 0, 0, 6, 0], [6, 0, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 6, 6, 0, 6]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 6, 0, 6, 0, 0, 0, 0], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 0, 0, 6, 6, 6, 6, 0], [0, 0, 0, 6, 0, 6, 0, 0]] -> [[7, 7, 7, 7, 7, 4, 4, 7], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 4, 7, 4, 7, 7, 7, 7], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 7, 7, 4, 4, 4, 4, 7], [0, 0, 0, 6, 0, 6, 0, 0]]\n",
+            "Replicate 1": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 6, 0, 0, 6, 0, 0], [6, 0, 0, 0, 6, 0, 6, 6], [0, 0, 0, 0, 0, 0, 0, 6], [0, 0, 0, 6, 0, 0, 0, 0], [7, 6, 0, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 6, 0], [6, 0, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 6, 6, 0, 6]] -> [[7, 7, 4, 7, 7, 4, 7, 7], [6, 0, 0, 0, 6, 0, 6, 6], [0, 0, 0, 0, 0, 0, 0, 6], [0, 0, 0, 6, 0, 0, 0, 0], [7, 4, 7, 4, 4, 7, 7, 7], [0, 6, 6, 0, 0, 0, 6, 0], [6, 0, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 6, 6, 0, 6]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [7, 6, 6, 0, 0, 0, 0, 0], [6, 0, 6, 0, 6, 0, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 4, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [7, 4, 4, 7, 7, 7, 7, 7], [6, 0, 6, 0, 6, 0, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 0, 0, 6, 6, 6, 0, 0], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 7, 4, 4, 4, 7, 7], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 6, 0, 0, 0, 0, 0, 0], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 4, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 4, 7, 7, 7, 7, 7, 7], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 2": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [7, 6, 6, 0, 0, 0, 0, 0], [6, 0, 6, 0, 6, 0, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 4, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 6, 6, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [7, 4, 4, 7, 7, 7, 7, 7], [6, 0, 6, 0, 6, 0, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 6, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 0, 0, 0, 6, 0, 0, 0], [0, 6, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 6, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 7, 7, 7, 4, 7, 7, 7], [0, 6, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 6, 0, 0, 0, 0, 0, 0], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 4, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 4, 7, 7, 7, 7, 7, 7], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 3": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 6, 0, 0, 0, 0, 0, 0], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 4, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 4, 7, 7, 7, 7, 7, 7], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 6, 0, 0, 0, 0, 0, 0], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 4, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 4, 7, 7, 7, 7, 7, 7], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 0, 0, 6, 6, 6, 0, 0], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 7, 4, 4, 4, 7, 7], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]]\n",
+            "Replicate 4": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 0, 0, 6, 6, 6, 0, 0], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 7, 4, 4, 4, 7, 7], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 6, 0, 6, 0, 0, 0, 0], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 0, 0, 6, 6, 6, 6, 0], [0, 0, 0, 6, 0, 6, 0, 0]] -> [[7, 7, 7, 7, 7, 4, 4, 7], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 4, 7, 4, 7, 7, 7, 7], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 7, 7, 4, 4, 4, 4, 7], [0, 0, 0, 6, 0, 6, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 6, 0, 0, 0, 0, 0, 0], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 4, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 0, 0, 6, 0], [0, 6, 6, 6, 0, 0, 6, 6], [7, 4, 7, 7, 7, 7, 7, 7], [0, 6, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 0, 6, 0, 6], [0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [0, 6, 0, 0, 0, 0, 0, 6], [6, 0, 6, 0, 0, 0, 0, 0], [7, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 6, 0, 0, 0, 0], [0, 0, 6, 0, 6, 0, 6, 6], [0, 0, 6, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 6, 0, 0, 0, 0, 6], [0, 6, 0, 0, 0, 0, 0, 6], [6, 0, 6, 0, 0, 0, 0, 0], [7, 7, 4, 7, 4, 7, 4, 7], [0, 6, 0, 6, 0, 0, 0, 0], [0, 0, 6, 0, 6, 0, 6, 6], [0, 0, 6, 0, 0, 0, 0, 0]]\n"
+        },
+        "L3": {
+            "Replicate 0": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [0, 6, 0, 0, 0, 0, 0, 6], [6, 0, 6, 0, 0, 0, 0, 0], [7, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 6, 0, 0, 0, 0], [0, 0, 6, 0, 6, 0, 6, 6], [0, 0, 6, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 6, 0, 0, 0, 0, 6], [0, 6, 0, 0, 0, 0, 0, 6], [6, 0, 6, 0, 0, 0, 0, 0], [7, 7, 4, 7, 4, 7, 4, 7], [0, 6, 0, 6, 0, 0, 0, 0], [0, 0, 6, 0, 6, 0, 6, 6], [0, 0, 6, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[7, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 6, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 0, 0, 0, 0, 0, 0, 0], [0, 6, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 6, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 7, 7, 7, 7, 7, 7, 7], [0, 6, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 6, 0, 6, 0, 0, 0, 0], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 0, 0, 6, 6, 6, 6, 0], [0, 0, 0, 6, 0, 6, 0, 0]] -> [[7, 7, 7, 7, 7, 4, 4, 7], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 4, 7, 4, 7, 7, 7, 7], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 7, 7, 4, 4, 4, 4, 7], [0, 0, 0, 6, 0, 6, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[7, 0, 0, 0, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [6, 6, 6, 6, 6, 6, 6, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [6, 6, 6, 6, 6, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]]\n",
+            "Replicate 1": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[7, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 2, 2, 0, 0, 0], [0, 0, 2, 0, 0, 0, 0, 2], [7, 0, 0, 0, 0, 0, 0, 0], [0, 2, 0, 0, 0, 2, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0], [7, 0, 0, 0, 2, 0, 0, 0], [0, 2, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [2, 0, 0, 2, 2, 0, 0, 0], [0, 0, 2, 0, 0, 0, 0, 2], [7, 7, 7, 7, 7, 7, 7, 7], [0, 2, 0, 0, 0, 2, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0], [7, 7, 7, 7, 4, 7, 7, 7], [0, 2, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 6, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 0, 0, 0, 6, 0, 0, 0], [0, 6, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 6, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 7, 7, 7, 4, 7, 7, 7], [0, 6, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]]\n",
+            "Replicate 2": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [0, 6, 6, 0, 6, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[7, 6, 6, 6, 6, 6, 6, 6], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 6, 6, 6, 6, 6, 6, 6], [0, 6, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 6, 6, 6, 6, 6, 6, 6], [0, 6, 0, 0, 0, 0, 0, 0]] -> [[7, 4, 4, 4, 4, 4, 4, 4], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 4, 4, 4, 4, 4, 4, 4], [0, 6, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 4, 4, 4, 4, 4, 4, 4], [0, 6, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 6, 0, 6, 0, 0, 0, 0], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 0, 0, 6, 6, 6, 6, 0], [0, 0, 0, 6, 0, 6, 0, 0]] -> [[7, 7, 7, 7, 7, 4, 4, 7], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 4, 7, 4, 7, 7, 7, 7], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 7, 7, 4, 4, 4, 4, 7], [0, 0, 0, 6, 0, 6, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[7, 0, 0, 0, 0, 0, 0, 2], [0, 0, 2, 0, 2, 0, 2, 0], [0, 2, 0, 0, 0, 0, 0, 0], [0, 0, 0, 2, 0, 0, 0, 2], [0, 2, 2, 0, 2, 0, 0, 2], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 2, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [0, 0, 2, 0, 2, 0, 2, 0], [0, 2, 0, 0, 0, 0, 0, 0], [0, 0, 0, 2, 0, 0, 0, 2], [0, 2, 2, 0, 2, 0, 0, 2], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 2, 0, 0, 0, 0]]\n",
+            "Replicate 3": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 6, 0, 0, 6, 0, 0], [6, 0, 0, 0, 6, 0, 6, 6], [0, 0, 0, 0, 0, 0, 0, 6], [0, 0, 0, 6, 0, 0, 0, 0], [7, 6, 0, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 6, 0], [6, 0, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 6, 6, 0, 6]] -> [[7, 7, 4, 7, 7, 4, 7, 7], [6, 0, 0, 0, 6, 0, 6, 6], [0, 0, 0, 0, 0, 0, 0, 6], [0, 0, 0, 6, 0, 0, 0, 0], [7, 4, 7, 4, 4, 7, 7, 7], [0, 6, 6, 0, 0, 0, 6, 0], [6, 0, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 6, 6, 0, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[7, 0, 0, 0, 0, 0, 0, 0], [8, 0, 0, 8, 8, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 8], [7, 0, 0, 0, 0, 0, 0, 0], [0, 8, 0, 0, 0, 8, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0], [7, 0, 0, 0, 8, 0, 0, 0], [0, 8, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [8, 0, 0, 8, 8, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 8], [7, 7, 7, 7, 7, 7, 7, 7], [0, 8, 0, 0, 0, 8, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0], [7, 7, 7, 7, 4, 7, 7, 7], [0, 8, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 6, 6, 0], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 6, 0, 6, 0, 0, 0, 0], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 0, 0, 6, 6, 6, 6, 0], [0, 0, 0, 6, 0, 6, 0, 0]] -> [[7, 7, 7, 7, 7, 4, 4, 7], [0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 4, 7, 4, 7, 7, 7, 7], [0, 6, 0, 6, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 0, 6], [7, 7, 7, 4, 4, 4, 4, 7], [0, 0, 0, 6, 0, 6, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[7, 0, 0, 0, 0, 0, 0, 6], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [6, 6, 6, 6, 6, 6, 6, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [0, 0, 6, 0, 6, 0, 6, 0], [0, 6, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 6], [6, 6, 6, 6, 6, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 6, 0, 0, 0, 0]]\n",
+            "Replicate 4": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[7, 0, 6, 0, 0, 6, 0, 0], [6, 0, 0, 0, 6, 0, 6, 6], [0, 0, 0, 0, 0, 0, 0, 6], [0, 0, 0, 6, 0, 0, 0, 0], [7, 6, 0, 6, 6, 0, 0, 0], [0, 6, 6, 0, 0, 0, 6, 0], [6, 0, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 6, 6, 0, 6]] -> [[7, 7, 4, 7, 7, 4, 7, 7], [6, 0, 0, 0, 6, 0, 6, 6], [0, 0, 0, 0, 0, 0, 0, 6], [0, 0, 0, 6, 0, 0, 0, 0], [7, 4, 7, 4, 4, 7, 7, 7], [0, 6, 6, 0, 0, 0, 6, 0], [6, 0, 0, 6, 0, 6, 0, 6], [0, 0, 0, 0, 6, 6, 0, 6]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[7, 0, 0, 0, 0, 0, 0, 0], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 0, 0, 0, 6, 0, 0, 0], [0, 6, 0, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 7], [6, 0, 0, 6, 6, 0, 0, 0], [0, 0, 6, 0, 0, 0, 0, 6], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0], [7, 7, 7, 7, 4, 7, 7, 7], [0, 6, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[7, 0, 0, 0, 0, 0, 0, 6], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 0, 0, 6, 6, 6, 0, 0], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [6, 0, 0, 6, 0, 0, 0, 0], [0, 6, 6, 0, 0, 0, 0, 0], [0, 0, 6, 0, 0, 6, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 7, 4, 4, 4, 7, 7], [6, 0, 0, 6, 0, 0, 0, 0], [6, 0, 6, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[7, 0, 0, 0, 0, 0, 0, 8], [0, 0, 8, 0, 8, 0, 8, 0], [0, 8, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 8], [0, 8, 8, 0, 8, 0, 0, 8], [7, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 0]] -> [[7, 7, 7, 7, 7, 7, 7, 4], [0, 0, 8, 0, 8, 0, 8, 0], [0, 8, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 8], [0, 8, 8, 0, 8, 0, 0, 8], [7, 7, 7, 7, 7, 7, 7, 7], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 8, 0, 0, 0, 0]]\n"
+        }
+    },
+    "SCMz750": {
+        "L1": {
+            "Replicate 0": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 8, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [6, 6, 6, 6, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 5, 0, 7, 0], [0, 9, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [9, 0, 5, 0, 0, 0, 0, 0, 7, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[9, 9, 5, 0, 2, 0, 5, 8, 7, 2], [9, 9, 5, 8, 2, 8, 5, 8, 7, 2], [9, 9, 5, 7, 2, 7, 7, 7, 7, 2], [9, 9, 5, 0, 2, 0, 0, 0, 7, 2], [9, 2, 5, 2, 2, 0, 0, 0, 7, 2], [9, 0, 5, 0, 0, 0, 0, 0, 7, 2], [7, 7, 7, 7, 7, 7, 7, 7, 7, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 8, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [6, 6, 6, 6, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [8, 8, 8, 8, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 1": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 5, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 5, 3], [0, 0, 5, 0, 0, 0, 0, 3, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 5, 0, 5, 8, 0, 4, 5, 3], [0, 0, 5, 0, 5, 8, 0, 4, 5, 3], [0, 0, 5, 0, 5, 8, 0, 4, 5, 3], [8, 8, 5, 8, 8, 8, 0, 4, 5, 3], [3, 3, 5, 3, 3, 3, 3, 4, 3, 3], [3, 3, 3, 3, 3, 3, 3, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [4, 4, 4, 4, 4, 4, 4, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 7, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 9, 0, 0, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0]] -> [[0, 0, 0, 7, 0, 6, 0, 0, 6, 0], [0, 0, 0, 7, 0, 6, 0, 0, 6, 0], [7, 7, 7, 7, 0, 6, 0, 0, 6, 0], [0, 0, 0, 0, 0, 6, 0, 0, 6, 0], [6, 6, 6, 6, 6, 6, 6, 6, 6, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [6, 6, 6, 6, 6, 6, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0, 0, 0, 8, 0, 0, 0, 0], [2, 0, 0, 0, 0, 8, 0, 0, 0, 0], [2, 0, 0, 0, 0, 8, 0, 0, 0, 0], [2, 8, 8, 8, 8, 8, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 2": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[3, 3, 3, 3, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 6, 6, 0, 0], [2, 2, 2, 2, 2, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[3, 3, 3, 3, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 6, 6, 0, 0], [2, 2, 2, 2, 2, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 3": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[3, 3, 3, 3, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 6, 6, 0, 0], [2, 2, 2, 2, 2, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 5, 0, 7, 0], [0, 9, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [9, 0, 5, 0, 0, 0, 0, 0, 7, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[9, 9, 5, 0, 2, 0, 5, 8, 7, 2], [9, 9, 5, 8, 2, 8, 5, 8, 7, 2], [9, 9, 5, 7, 2, 7, 7, 7, 7, 2], [9, 9, 5, 0, 2, 0, 0, 0, 7, 2], [9, 2, 5, 2, 2, 0, 0, 0, 7, 2], [9, 0, 5, 0, 0, 0, 0, 0, 7, 2], [7, 7, 7, 7, 7, 7, 7, 7, 7, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[3, 3, 3, 3, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 6, 6, 0, 0], [2, 2, 2, 2, 2, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 4": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs as demonstration. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[3, 3, 3, 3, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 6, 6, 0, 0], [2, 2, 2, 2, 2, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 7, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 9, 0, 0, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0]] -> [[0, 0, 0, 7, 0, 6, 0, 0, 6, 0], [0, 0, 0, 7, 0, 6, 0, 0, 6, 0], [7, 7, 7, 7, 0, 6, 0, 0, 6, 0], [0, 0, 0, 0, 0, 6, 0, 0, 6, 0], [6, 6, 6, 6, 6, 6, 6, 6, 6, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [6, 6, 6, 6, 6, 6, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 6, 0, 0, 0, 0, 0, 8, 0, 0], [0, 0, 0, 0, 0, 0, 5, 0, 7, 0], [0, 9, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 2, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [9, 0, 5, 0, 0, 0, 0, 0, 7, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[9, 9, 5, 0, 2, 0, 5, 8, 7, 2], [9, 9, 5, 8, 2, 8, 5, 8, 7, 2], [9, 9, 5, 7, 2, 7, 7, 7, 7, 2], [9, 9, 5, 0, 2, 0, 0, 0, 7, 2], [9, 2, 5, 2, 2, 0, 0, 0, 7, 2], [9, 0, 5, 0, 0, 0, 0, 0, 7, 2], [7, 7, 7, 7, 7, 7, 7, 7, 7, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n"
+        },
+        "L3": {
+            "Replicate 0": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 7, 0, 0, 0, 0, 0, 0, 0, 0], [7, 7, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [8, 8, 8, 8, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 7, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 9, 0, 0, 6, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0]] -> [[0, 0, 0, 7, 0, 6, 0, 0, 6, 0], [0, 0, 0, 7, 0, 6, 0, 0, 6, 0], [7, 7, 7, 7, 0, 6, 0, 0, 6, 0], [0, 0, 0, 0, 0, 6, 0, 0, 6, 0], [6, 6, 6, 6, 6, 6, 6, 6, 6, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [0, 0, 0, 0, 0, 6, 0, 0, 0, 0], [6, 6, 6, 6, 6, 6, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 5, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 5, 2], [0, 0, 5, 0, 0, 0, 0, 2, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 5, 0, 5, 8, 0, 4, 5, 2], [0, 0, 5, 0, 5, 8, 0, 4, 5, 2], [0, 0, 5, 0, 5, 8, 0, 4, 5, 2], [8, 8, 5, 8, 8, 8, 0, 4, 5, 2], [2, 2, 5, 2, 2, 2, 2, 4, 2, 2], [2, 2, 2, 2, 2, 2, 2, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [4, 4, 4, 4, 4, 4, 4, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 1": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 0, 0, 0, 8, 0, 0, 0, 0], [2, 0, 0, 0, 0, 8, 0, 0, 0, 0], [2, 0, 0, 0, 0, 8, 0, 0, 0, 0], [2, 8, 8, 8, 8, 8, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 7, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0, 7, 0, 0, 0, 0, 0], [0, 0, 0, 0, 7, 0, 0, 0, 0, 0], [0, 0, 0, 0, 7, 0, 0, 0, 0, 0], [0, 0, 0, 0, 7, 0, 0, 0, 0, 0], [0, 0, 0, 0, 7, 0, 0, 0, 0, 0], [8, 8, 8, 8, 7, 0, 0, 0, 0, 0], [0, 0, 0, 0, 7, 0, 0, 0, 0, 0], [7, 7, 7, 7, 7, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [8, 8, 8, 8, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 5, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 5, 3], [0, 0, 5, 0, 0, 0, 0, 3, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 5, 0, 5, 8, 0, 3, 5, 3], [0, 0, 5, 0, 5, 8, 0, 3, 5, 3], [0, 0, 5, 0, 5, 8, 0, 3, 5, 3], [8, 8, 5, 8, 8, 8, 0, 3, 5, 3], [3, 3, 5, 3, 3, 3, 3, 3, 3, 3], [3, 3, 3, 3, 3, 3, 3, 3, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 2": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 6, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[3, 3, 3, 3, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [0, 0, 0, 0, 3, 2, 0, 6, 0, 0], [6, 6, 6, 6, 3, 2, 6, 6, 0, 0], [2, 2, 2, 2, 2, 2, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [8, 8, 8, 8, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [3, 3, 3, 3, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 8, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [6, 6, 6, 6, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by fixing some values.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 3], [0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0, 0, 8, 0, 4, 0, 3], [0, 0, 0, 0, 0, 8, 0, 4, 0, 3], [0, 0, 0, 0, 0, 8, 0, 4, 0, 3], [8, 8, 8, 8, 8, 8, 0, 4, 0, 3], [3, 3, 3, 3, 3, 3, 3, 4, 3, 3], [3, 3, 3, 3, 3, 3, 3, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [4, 4, 4, 4, 4, 4, 4, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 3": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 8, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [6, 6, 6, 6, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [8, 8, 8, 8, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [3, 3, 3, 3, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 8, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [6, 6, 6, 6, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 5, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 5, 2], [0, 0, 5, 0, 0, 0, 0, 2, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 5, 0, 5, 8, 0, 4, 5, 2], [0, 0, 5, 0, 5, 8, 0, 4, 5, 2], [0, 0, 5, 0, 5, 8, 0, 4, 5, 2], [8, 8, 5, 8, 8, 8, 0, 4, 5, 2], [2, 2, 5, 2, 2, 2, 2, 4, 2, 2], [2, 2, 2, 2, 2, 2, 2, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [4, 4, 4, 4, 4, 4, 4, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n",
+            "Replicate 4": "You must solve the following puzzle by discovering the deterministic rule that maps inputs to outputs. Both the inputs and outputs are 2D Python arrays of colored pixels. We provide example input-output pairs along with counterfactual examples, which represent interventions on the original examples. To solve the problem, express the deterministic rule as a Python program. Do not explain your reasoning, and only output a single Python program.\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 8, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 8, 0, 0, 0, 6, 0, 0, 0], [2, 8, 8, 0, 0, 0, 6, 0, 0, 0], [2, 0, 0, 0, 0, 0, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 6, 0, 0, 0], [6, 6, 6, 6, 6, 6, 6, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 8, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [8, 8, 8, 8, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [3, 3, 3, 3, 3, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nExample input-output arrays:\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 5, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 5, 3], [0, 0, 5, 0, 0, 0, 0, 3, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 5, 0, 5, 8, 0, 4, 5, 3], [0, 0, 5, 0, 5, 8, 0, 4, 5, 3], [0, 0, 5, 0, 5, 8, 0, 4, 5, 3], [8, 8, 5, 8, 8, 8, 0, 4, 5, 3], [3, 3, 5, 3, 3, 3, 3, 4, 3, 3], [3, 3, 3, 3, 3, 3, 3, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [4, 4, 4, 4, 4, 4, 4, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\nCounterfactual: Now imagine that we intervened on the previous input by changing some colors.\n[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 5, 8, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 5, 1], [0, 0, 5, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]] -> [[0, 0, 5, 0, 5, 8, 0, 4, 5, 1], [0, 0, 5, 0, 5, 8, 0, 4, 5, 1], [0, 0, 5, 0, 5, 8, 0, 4, 5, 1], [8, 8, 5, 8, 8, 8, 0, 4, 5, 1], [1, 1, 5, 1, 1, 1, 1, 4, 1, 1], [1, 1, 1, 1, 1, 1, 1, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 4, 0, 0], [4, 4, 4, 4, 4, 4, 4, 4, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]\n"
+        }
+    }
+}

static_evaluation_set/v0_09-01-25/.ipynb_checkpoints/consolidate_dicts-checkpoint.ipynb

@@ -0,0 +1,1634 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "fa9c1378-c372-4979-81aa-51b3189073d9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "python version     : 3.12.2\n",
+      "numpy version      : 1.26.4\n",
+      "pandas version     : 2.2.3\n",
+      "matplotlib version : 3.10.0\n",
+      "seaborn version    : 0.13.2\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib import colors\n",
+    "import seaborn as sns\n",
+    "import json\n",
+    "import platform\n",
+    "import ast\n",
+    "from itertools import permutations,product\n",
+    "from ast import literal_eval\n",
+    "import os\n",
+    "from os import listdir\n",
+    "from os.path import isfile, join\n",
+    "\n",
+    "# Custom modules.\n",
+    "os.chdir(\"../../../causal_arc\")\n",
+    "from carc_utils import UtilsARC\n",
+    "from carc_augment import AugmentARC\n",
+    "from carc import CausalARC\n",
+    "from carc_tasks_logical import TaskLogical\n",
+    "\n",
+    "# View versioning.\n",
+    "print(\"python version     :\", platform.python_version())\n",
+    "print(\"numpy version      :\", np.__version__)\n",
+    "print(\"pandas version     :\", pd.__version__)\n",
+    "print(\"matplotlib version :\", matplotlib.__version__)\n",
+    "print(\"seaborn version    :\", sns.__version__)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "235289fb-6c90-47c8-a08f-0dffb7325337",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "os.chdir(\"../data/static_evaluation_set/v0_09-01-25/\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9643e5b3-6c04-43b5-a9da-72504b70b89b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['causal_arc_logical_or.json', 'causal_arc_logical_compose.json', 'causal_arc_logical_alternate.json', 'causal_arc_logical_25x25.json', 'causal_arc_logical_xor.json', 'causal_arc_logical_solutions.json', 'causal_arc_logical_and.json']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Load JSON files.\n",
+    "counting_file = \"counting/causal_arc_counting.json\"\n",
+    "with open(counting_file) as json_file:\n",
+    "    counting_dict = json.load(json_file)\n",
+    "\n",
+    "extension_file = \"extension/causal_arc_extension.json\"\n",
+    "with open(extension_file) as json_file:\n",
+    "    extension_dict = json.load(json_file)\n",
+    "\n",
+    "ordering_file = \"ordering/causal_arc_ordering.json\"\n",
+    "with open(ordering_file) as json_file:\n",
+    "    ordering_dict = json.load(json_file)\n",
+    "\n",
+    "# Logical tasks.\n",
+    "path = \"logical/\"\n",
+    "logical_files = [f for f in listdir(path) if isfile(join(path, f))]\n",
+    "print(logical_files)\n",
+    "logical_dicts = []\n",
+    "for f in logical_files:\n",
+    "    if \"solutions\" not in f:\n",
+    "        with open(path+f) as json_file:\n",
+    "            logical_dicts.append(json.load(json_file))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a8378519-f675-4954-9338-68a2156bd04c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['SCMm5ob_10x10', 'SCMm5ob_15x15', 'SCMm5ob_20x20', 'SCMev5t_10x10', 'SCMev5t_15x15', 'SCMev5t_20x20', 'SCMfuy3', 'SCMhlh2', 'SCM43rz', 'SCM95ls'])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "counting_dict.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "42b4b59b-3fa6-4657-99aa-5c01baa833ba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#logical_dicts[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fc29f390-7ec8-4d11-b984-8687599b6f0d",
+   "metadata": {},
+   "source": [
+    "# Counting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "b9453aec-e917-4bae-af91-28faa5c8d935",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "def SCMm5ob(colors: list):\n",
+      "            p = [0.8]+[0.05]*4\n",
+      "            x = np.random.choice(colors, size = size, replace = True, p = p)\n",
+      "            \n",
+      "            counts = np.unique(x, return_counts = True)\n",
+      "            y = np.zeros((np.max(counts[1][1:]), 4)).astype(int)\n",
+      "            counts = dict(zip(counts[0], counts[1]))\n",
+      "            for color,count in counts.items():\n",
+      "                if color > 0:\n",
+      "                    y[-count:,colors.index(color)-1] = color\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMm5ob(colors: list):\n",
+      "            p = [0.8]+[0.05]*4\n",
+      "            x = np.random.choice(colors, size = size, replace = True, p = p)\n",
+      "            \n",
+      "            counts = np.unique(x, return_counts = True)\n",
+      "            y = np.zeros((np.max(counts[1][1:]), 4)).astype(int)\n",
+      "            counts = dict(zip(counts[0], counts[1]))\n",
+      "            for color,count in counts.items():\n",
+      "                if color > 0:\n",
+      "                    y[-count:,colors.index(color)-1] = color\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMm5ob(colors: list):\n",
+      "            p = [0.8]+[0.05]*4\n",
+      "            x = np.random.choice(colors, size = size, replace = True, p = p)\n",
+      "            \n",
+      "            counts = np.unique(x, return_counts = True)\n",
+      "            y = np.zeros((np.max(counts[1][1:]), 4)).astype(int)\n",
+      "            counts = dict(zip(counts[0], counts[1]))\n",
+      "            for color,count in counts.items():\n",
+      "                if color > 0:\n",
+      "                    y[-count:,colors.index(color)-1] = color\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMev5t(colors: list, size: tuple = (10,10)):\n",
+      "            n_per_color = np.random.choice([1,2,3], size = len(colors))\n",
+      "            true_n_per_color = [x for x in n_per_color]\n",
+      "            x = np.zeros(size).astype(int)\n",
+      "            for i in range(len(colors)):\n",
+      "                for n in range(n_per_color[i]):\n",
+      "                    try:\n",
+      "                        random_size = np.random.choice([2,3], size = 2)\n",
+      "                        sprite = np.ones(random_size).astype(int)*colors[i]\n",
+      "                        x = self.a.add_sprite(x, sprite = sprite)\n",
+      "                    except:\n",
+      "                        if true_n_per_color[i] == 0:\n",
+      "                            pass\n",
+      "                        else: \n",
+      "                            true_n_per_color[i] -= 1\n",
+      "\n",
+      "            sorted_vals = sorted(zip(true_n_per_color,colors))\n",
+      "            sorted_vals = [x for x in sorted_vals if x[0] > 0]\n",
+      "            y = np.zeros((len(sorted_vals), max(true_n_per_color))).astype(int)\n",
+      "            for i in range(len(sorted_vals)):\n",
+      "                y[i,:sorted_vals[i][0]] = sorted_vals[i][1]\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMev5t(colors: list, size: tuple = (10,10)):\n",
+      "            n_per_color = np.random.choice([1,2,3], size = len(colors))\n",
+      "            true_n_per_color = [x for x in n_per_color]\n",
+      "            x = np.zeros(size).astype(int)\n",
+      "            for i in range(len(colors)):\n",
+      "                for n in range(n_per_color[i]):\n",
+      "                    try:\n",
+      "                        random_size = np.random.choice([2,3], size = 2)\n",
+      "                        sprite = np.ones(random_size).astype(int)*colors[i]\n",
+      "                        x = self.a.add_sprite(x, sprite = sprite)\n",
+      "                    except:\n",
+      "                        if true_n_per_color[i] == 0:\n",
+      "                            pass\n",
+      "                        else: \n",
+      "                            true_n_per_color[i] -= 1\n",
+      "\n",
+      "            sorted_vals = sorted(zip(true_n_per_color,colors))\n",
+      "            sorted_vals = [x for x in sorted_vals if x[0] > 0]\n",
+      "            y = np.zeros((len(sorted_vals), max(true_n_per_color))).astype(int)\n",
+      "            for i in range(len(sorted_vals)):\n",
+      "                y[i,:sorted_vals[i][0]] = sorted_vals[i][1]\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMev5t(colors: list, size: tuple = (10,10)):\n",
+      "            n_per_color = np.random.choice([1,2,3], size = len(colors))\n",
+      "            true_n_per_color = [x for x in n_per_color]\n",
+      "            x = np.zeros(size).astype(int)\n",
+      "            for i in range(len(colors)):\n",
+      "                for n in range(n_per_color[i]):\n",
+      "                    try:\n",
+      "                        random_size = np.random.choice([2,3], size = 2)\n",
+      "                        sprite = np.ones(random_size).astype(int)*colors[i]\n",
+      "                        x = self.a.add_sprite(x, sprite = sprite)\n",
+      "                    except:\n",
+      "                        if true_n_per_color[i] == 0:\n",
+      "                            pass\n",
+      "                        else: \n",
+      "                            true_n_per_color[i] -= 1\n",
+      "\n",
+      "            sorted_vals = sorted(zip(true_n_per_color,colors))\n",
+      "            sorted_vals = [x for x in sorted_vals if x[0] > 0]\n",
+      "            y = np.zeros((len(sorted_vals), max(true_n_per_color))).astype(int)\n",
+      "            for i in range(len(sorted_vals)):\n",
+      "                y[i,:sorted_vals[i][0]] = sorted_vals[i][1]\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMfuy3():\n",
+      "            size = (3,3)\n",
+      "            half = total_colors//2\n",
+      "            colors = np.random.choice(list(range(1,10)), replace = False, size = half).tolist()\n",
+      "            not_in = [x for x in list(range(1,10)) if x not in colors]\n",
+      "            most_freq_color = np.random.choice(not_in, replace = False, size = 1)[0]\n",
+      "            most_freq = [most_freq_color for i in range(half)]\n",
+      "            colors = colors + most_freq\n",
+      "            random.shuffle(colors)\n",
+      "            u_list = [np.random.binomial(n = 1, p = 0.85, size = size) for i in range(len(colors))]\n",
+      "            x = [u_list[i]*colors[i] for i in range(len(colors))]\n",
+      "            x = [np.pad(z, pad_width = 1) for z in x]\n",
+      "            x = np.concatenate(x, axis = 1)\n",
+      "            y = [np.pad(np.ones((1,1)),pad_width=1)*colors[i] if colors[i] != most_freq_color else np.ones(size)*most_freq_color for i in range(len(colors))]\n",
+      "            y = np.concatenate(y, axis = 0)\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMhlh2():\n",
+      "            size = np.random.choice(range(3,10), size = 2)\n",
+      "            colors = np.random.choice(range(2,10), size = 2, replace = False)\n",
+      "            _u = np.random.binomial(n = 1, p = 0.8, size = size)\n",
+      "            x = _u.copy()\n",
+      "            count = x[0,0]+x[-1,0]+x[0,-1]+x[-1,-1]\n",
+      "            x[0,0] = x[0,0]*colors[0]\n",
+      "            x[-1,0] = x[-1,0]*colors[0]\n",
+      "            x[0,-1] = x[0,-1]*colors[0]\n",
+      "            x[-1,-1] = x[-1,-1]*colors[0]\n",
+      "            x[x.shape[0]//2,x.shape[1]//2] = colors[1]\n",
+      "            y = np.ones((1,count)).astype(int)*colors[1]\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCM43rz():\n",
+      "            colors = np.random.choice([1,2,3,4], size = 2, replace = False)\n",
+      "            u1 = np.random.binomial(n = 1, size = (5,5), p = 0.5)\n",
+      "            u2 = np.random.binomial(n = 1, size = (5,5), p = 0.5)\n",
+      "            x = u1*colors[0] + u2*colors[1]\n",
+      "            x = np.pad(x, pad_width = 2)\n",
+      "            counts = np.unique(x, return_counts = True)\n",
+      "            # Getting sorted indices.\n",
+      "            idx = np.argsort(counts[1]) \n",
+      "            # Sorting both lists.\n",
+      "            colors = [counts[0][i] for i in idx] \n",
+      "            counts = [counts[1][i] for i in idx] \n",
+      "            least_freq = [colors[i] for i in range(len(colors)) if counts[i] == min(counts)]\n",
+      "            y = np.array(least_freq).reshape(-1,1)\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCM95ls():\n",
+      "            sprites = []\n",
+      "            n = np.random.choice([2,3,4], size = 1)[0]\n",
+      "            colors = np.random.choice([1,2,3,4,6,7,8,9], size = n, replace = False)\n",
+      "            for i in range(n):\n",
+      "                sprite = np.random.binomial(n = 1, size = (3,3), p = 0.8)*colors[i]\n",
+      "                sprite = np.pad(sprite, pad_width = 1)\n",
+      "                sprites.append(sprite)\n",
+      "            x = np.concatenate(sprites, axis = 1)\n",
+      "            y = np.concatenate([np.repeat(s,n,axis=1) for s in sprites], axis = 1)\n",
+      "            return x,y\n",
+      "        \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for task,task_dict in counting_dict.items():\n",
+    "    scm_name = task.split(\"_\")[0]\n",
+    "    scm = task_dict[\"scm\"].replace(\"get_xy\", scm_name)\n",
+    "    scm = scm.replace(\"\\n    def\", \"def\")\n",
+    "    scm = scm.replace(\"(colors):\", \"(colors: list):\")\n",
+    "    task_dict[\"scm\"] = scm\n",
+    "    print(scm)\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14540505-61f9-4898-bbcb-80364c8726f7",
+   "metadata": {},
+   "source": [
+    "# Extension"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "d3a4cd94-cff9-4a1c-b796-14130c900de2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "def SCMfwpq(colors: list = [6,7,4], size: tuple = (8,8)):\n",
+      "            _u = np.random.binomial(n = 1, p = 0.25, size = size)\n",
+      "            x = colors[0]*_u\n",
+      "            for i in range(x.shape[0]):\n",
+      "                if i % modulo == 0:\n",
+      "                    x[i,0] = colors[1]\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if (i % modulo == 0) and (x[i,j] == 0):\n",
+      "                        y[i,j] = colors[1]\n",
+      "                    elif (i % modulo == 0) and (x[i,j] == colors[0]):\n",
+      "                        y[i,j] = colors[2]\n",
+      "                    else:\n",
+      "                        y[i,j] = x[i,j]\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMig1o(colors: list = [6,7,4], size: tuple = (10,10), modulo: int = 5):\n",
+      "            _u = np.random.binomial(n = 1, p = 0.25, size = size)\n",
+      "            x = colors[0]*_u\n",
+      "            for i in range(x.shape[1]):\n",
+      "                if i % modulo == 0:\n",
+      "                    x[0,i] = colors[1]\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if (j % modulo == 0) and (x[i,j] == 0):\n",
+      "                        y[i,j] = colors[1]\n",
+      "                    elif (j % modulo == 0) and (x[i,j] == colors[0]):\n",
+      "                        y[i,j] = colors[2]\n",
+      "                    else:\n",
+      "                        y[i,j] = x[i,j]\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMz750(size: tuple = (10,10)):\n",
+      "            x = np.random.choice(range(10), p = [0.955]+[0.005]*9, size = size)\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if x[i,j] != 0:\n",
+      "                        y[i,:j] = x[i,j] \n",
+      "                        y[:i,j] = x[i,j]\n",
+      "                    else:\n",
+      "                        y[i,j] = x[i,j] \n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMz750(size: tuple = (10,10)):\n",
+      "            x = np.random.choice(range(10), p = [0.955]+[0.005]*9, size = size)\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if x[i,j] != 0:\n",
+      "                        y[i,:j] = x[i,j] \n",
+      "                        y[:i,j] = x[i,j]\n",
+      "                    else:\n",
+      "                        y[i,j] = x[i,j] \n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMz750(size: tuple = (10,10)):\n",
+      "            x = np.random.choice(range(10), p = [0.955]+[0.005]*9, size = size)\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if x[i,j] != 0:\n",
+      "                        y[i,:j] = x[i,j] \n",
+      "                        y[:i,j] = x[i,j]\n",
+      "                    else:\n",
+      "                        y[i,j] = x[i,j] \n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCM6cjq(size: tuple = (10,10)):\n",
+      "            u1 = np.random.binomial(n = 1, p = 0.2, size = size)\n",
+      "            u2 = np.random.binomial(n = 1, p = 0.1, size = size)\n",
+      "            x = 6*u1 + u2\n",
+      "            y = x.copy()\n",
+      "            orange = np.argwhere(y==7)\n",
+      "            for idx in orange:\n",
+      "                y[idx[0]+1:,idx[1]] = 4\n",
+      "                y[idx[0],idx[1]] = 3\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMesea(size: tuple = (10,10), x: np.array = None):\n",
+      "            if x is None:\n",
+      "                _u = np.random.binomial(n = 1, p = 0.1, size = size)*5\n",
+      "                x = np.random.choice(range(10), p = [0.91]+[0.01]*9, size = size)\n",
+      "                x = x+_u\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in reversed(range(y.shape[1])):\n",
+      "                    if y[i,j] not in [0,5]:\n",
+      "                        y[i,j:] = x[i,j]\n",
+      "                    else:\n",
+      "                        y[i,j] = x[i,j] \n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMesea(size: tuple = (10,10), x: np.array = None):\n",
+      "            if x is None:\n",
+      "                _u = np.random.binomial(n = 1, p = 0.1, size = size)*5\n",
+      "                x = np.random.choice(range(10), p = [0.91]+[0.01]*9, size = size)\n",
+      "                x = x+_u\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in reversed(range(y.shape[1])):\n",
+      "                    if y[i,j] not in [0,5]:\n",
+      "                        y[i,j:] = x[i,j]\n",
+      "                    else:\n",
+      "                        y[i,j] = x[i,j] \n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMwoev(size: tuple = (10,10), x: np.array = None):\n",
+      "            if x is None:\n",
+      "                _u = np.random.binomial(n = 1, p = 0.05, size = size)*5\n",
+      "                x = np.random.choice(range(10), p = [0.955]+[0.005]*9, size = size)\n",
+      "                x = x+_u\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                not_black = np.argwhere(y[i,:]>0)\n",
+      "                for idx_list in not_black:\n",
+      "                    for idx in idx_list:\n",
+      "                        if x[i,idx] != 5:\n",
+      "                            y[i,idx:] = x[i,idx]\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMwoev(size: tuple = (10,10), x: np.array = None):\n",
+      "            if x is None:\n",
+      "                _u = np.random.binomial(n = 1, p = 0.05, size = size)*5\n",
+      "                x = np.random.choice(range(10), p = [0.955]+[0.005]*9, size = size)\n",
+      "                x = x+_u\n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                not_black = np.argwhere(y[i,:]>0)\n",
+      "                for idx_list in not_black:\n",
+      "                    for idx in idx_list:\n",
+      "                        if x[i,idx] != 5:\n",
+      "                            y[i,idx:] = x[i,idx]\n",
+      "            return x,y\n",
+      "        \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for task,task_dict in extension_dict.items():\n",
+    "    scm_name = task.split(\"!\")[0]\n",
+    "    scm = task_dict[\"scm\"].replace(\"get_xy\", scm_name)\n",
+    "    scm = scm.replace(\"\\n        def\", \"def\")\n",
+    "    scm = scm.replace(\"(colors):\", \"(colors: list):\")\n",
+    "    task_dict[\"scm\"] = scm\n",
+    "    print(scm)\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "02b2d14a-7a44-474c-81c6-6b79eb890677",
+   "metadata": {},
+   "source": [
+    "# Ordering"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "3e13266e-8f99-4ee9-b528-f7e186195565",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "def SCMv4bg(size: tuple = (10,9)):\n",
+      "            _u = np.random.binomial(n = 1, p = 0.6, size = size)\n",
+      "            x = 9*_u\n",
+      "            y = x.copy()\n",
+      "            for j in range(y.shape[1]):\n",
+      "                y[:,j][y[:,j] == 0] = j\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMv4bg(size: tuple = (10,9)):\n",
+      "            _u = np.random.binomial(n = 1, p = 0.6, size = size)\n",
+      "            x = 9*_u\n",
+      "            y = x.copy()\n",
+      "            for j in range(y.shape[1]):\n",
+      "                y[:,j][y[:,j] == 0] = j\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMye7g(n: int = 10):\n",
+      "            size = (n-2,n)\n",
+      "            colors = list(range(1,10))\n",
+      "            order = np.random.choice(colors, \n",
+      "                                     size = 3, #np.random.randint(low = 3, high = 7),\n",
+      "                                     replace = False)\n",
+      "            final_row = list(order)+[0]*(n-len(order))\n",
+      "            \n",
+      "            x = np.zeros(size).astype(int)\n",
+      "            for i in range(0,size[0],2):\n",
+      "                j = np.random.randint(low = 0, high = size[1])\n",
+      "                x[i,j] = np.random.choice(order, size = 1)[0]\n",
+      "            x = np.concatenate((x,np.zeros((1,n)))).astype(int)\n",
+      "            x = np.concatenate((x,np.array(final_row).reshape(1,-1)), axis = 0)\n",
+      "            \n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if y[i,j] == 0:\n",
+      "                        continue\n",
+      "                    elif y[i,j] == order[0]:\n",
+      "                        try:\n",
+      "                            y[i,j+1] = order[1]\n",
+      "                            y[i,j+2] = order[2]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "                    elif y[i,j] == order[1]:\n",
+      "                        try:\n",
+      "                            y[i,j+1] = order[2]\n",
+      "                            y[i,j-1] = order[0]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "                    elif y[i,j] == order[2]:\n",
+      "                        try:\n",
+      "                            y[i,j-1] = order[1]\n",
+      "                            y[i,j-2] = order[0]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMye7g(n: int = 10):\n",
+      "            size = (n-2,n)\n",
+      "            colors = list(range(1,10))\n",
+      "            order = np.random.choice(colors, \n",
+      "                                     size = 3, #np.random.randint(low = 3, high = 7),\n",
+      "                                     replace = False)\n",
+      "            final_row = list(order)+[0]*(n-len(order))\n",
+      "            \n",
+      "            x = np.zeros(size).astype(int)\n",
+      "            for i in range(0,size[0],2):\n",
+      "                j = np.random.randint(low = 0, high = size[1])\n",
+      "                x[i,j] = np.random.choice(order, size = 1)[0]\n",
+      "            x = np.concatenate((x,np.zeros((1,n)))).astype(int)\n",
+      "            x = np.concatenate((x,np.array(final_row).reshape(1,-1)), axis = 0)\n",
+      "            \n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if y[i,j] == 0:\n",
+      "                        continue\n",
+      "                    elif y[i,j] == order[0]:\n",
+      "                        try:\n",
+      "                            y[i,j+1] = order[1]\n",
+      "                            y[i,j+2] = order[2]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "                    elif y[i,j] == order[1]:\n",
+      "                        try:\n",
+      "                            y[i,j+1] = order[2]\n",
+      "                            y[i,j-1] = order[0]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "                    elif y[i,j] == order[2]:\n",
+      "                        try:\n",
+      "                            y[i,j-1] = order[1]\n",
+      "                            y[i,j-2] = order[0]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMye7g(n: int = 10):\n",
+      "            size = (n-2,n)\n",
+      "            colors = list(range(1,10))\n",
+      "            order = np.random.choice(colors, \n",
+      "                                     size = 3, #np.random.randint(low = 3, high = 7),\n",
+      "                                     replace = False)\n",
+      "            final_row = list(order)+[0]*(n-len(order))\n",
+      "            \n",
+      "            x = np.zeros(size).astype(int)\n",
+      "            for i in range(0,size[0],2):\n",
+      "                j = np.random.randint(low = 0, high = size[1])\n",
+      "                x[i,j] = np.random.choice(order, size = 1)[0]\n",
+      "            x = np.concatenate((x,np.zeros((1,n)))).astype(int)\n",
+      "            x = np.concatenate((x,np.array(final_row).reshape(1,-1)), axis = 0)\n",
+      "            \n",
+      "            y = x.copy()\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if y[i,j] == 0:\n",
+      "                        continue\n",
+      "                    elif y[i,j] == order[0]:\n",
+      "                        try:\n",
+      "                            y[i,j+1] = order[1]\n",
+      "                            y[i,j+2] = order[2]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "                    elif y[i,j] == order[1]:\n",
+      "                        try:\n",
+      "                            y[i,j+1] = order[2]\n",
+      "                            y[i,j-1] = order[0]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "                    elif y[i,j] == order[2]:\n",
+      "                        try:\n",
+      "                            y[i,j-1] = order[1]\n",
+      "                            y[i,j-2] = order[0]\n",
+      "                        except:\n",
+      "                            pass\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMswcs(n: int = 4):\n",
+      "            input_grids = []\n",
+      "            output_grids = []\n",
+      "            for i in range(n):\n",
+      "                _u = np.random.choice(list(range(1,10)), size = (2,2), replace = False)\n",
+      "                x = np.pad(_u, pad_width = 1)\n",
+      "                y = x.copy()\n",
+      "                y[0,0] = x[1,1]\n",
+      "                y[3,0] = x[2,1]\n",
+      "                y[0,3] = x[1,2]\n",
+      "                y[3,3] = x[2,2]\n",
+      "                input_grids.append(x)\n",
+      "                output_grids.append(y)\n",
+      "            x = np.concatenate(input_grids, axis = 1)\n",
+      "            y = np.concatenate(output_grids, axis = 1)\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMtzlq(n: int = 8, size: tuple = (20,20)):\n",
+      "            sprites = []\n",
+      "            order_row = np.zeros((2,size[1])).astype(int)\n",
+      "            order = np.random.choice(range(1,10), size = n, replace = False)\n",
+      "            order_row[1,:n] = order\n",
+      "            \n",
+      "            x = np.zeros((size[0]-2,size[1])).astype(int)\n",
+      "            for i in range(n):\n",
+      "                sprite = np.random.binomial(n = 1, size = (3,3), p = 0.8)*order[i]\n",
+      "                sprites.append(sprite)\n",
+      "                x = self.a.add_sprite(input_grid = x, sprite = sprite)\n",
+      "            x = np.concatenate((x,order_row))\n",
+      "            y = np.concatenate(sprites, axis = 1)\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMtzlq(n: int = 8, size: tuple = (20,20)):\n",
+      "            sprites = []\n",
+      "            order_row = np.zeros((2,size[1])).astype(int)\n",
+      "            order = np.random.choice(range(1,10), size = n, replace = False)\n",
+      "            order_row[1,:n] = order\n",
+      "            \n",
+      "            x = np.zeros((size[0]-2,size[1])).astype(int)\n",
+      "            for i in range(n):\n",
+      "                sprite = np.random.binomial(n = 1, size = (3,3), p = 0.8)*order[i]\n",
+      "                sprites.append(sprite)\n",
+      "                x = self.a.add_sprite(input_grid = x, sprite = sprite)\n",
+      "            x = np.concatenate((x,order_row))\n",
+      "            y = np.concatenate(sprites, axis = 1)\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMtzlq(n: int = 8, size: tuple = (20,20)):\n",
+      "            sprites = []\n",
+      "            order_row = np.zeros((2,size[1])).astype(int)\n",
+      "            order = np.random.choice(range(1,10), size = n, replace = False)\n",
+      "            order_row[1,:n] = order\n",
+      "            \n",
+      "            x = np.zeros((size[0]-2,size[1])).astype(int)\n",
+      "            for i in range(n):\n",
+      "                sprite = np.random.binomial(n = 1, size = (3,3), p = 0.8)*order[i]\n",
+      "                sprites.append(sprite)\n",
+      "                x = self.a.add_sprite(input_grid = x, sprite = sprite)\n",
+      "            x = np.concatenate((x,order_row))\n",
+      "            y = np.concatenate(sprites, axis = 1)\n",
+      "            return x,y\n",
+      "        \n",
+      "\n",
+      "def SCMffb8():\n",
+      "            sprite_sizes = [1,2,3,4]\n",
+      "            order = np.random.choice([1,2,3,4,6,7,8,9], size = 4, replace = False)\n",
+      "            order_rows = np.zeros((4,size[1])).astype(int)\n",
+      "            order_rows[-1,0] = order[0]\n",
+      "            order_rows[-2:,1] = order[1]\n",
+      "            order_rows[-3:,2] = order[2]\n",
+      "            order_rows[-4:,3] = order[3]\n",
+      "            x = np.zeros((size[0]-4,size[1])).astype(int)\n",
+      "            sprites = []\n",
+      "            for i in range(len(sprite_sizes)):\n",
+      "                if sprite_sizes[i] == 1:\n",
+      "                    sprite = np.array([[order[i]]])\n",
+      "                elif sprite_sizes[i] == 2:\n",
+      "                    sprite = np.ones((2,2)).astype(int)*order[i]\n",
+      "                else:\n",
+      "                    sprite = np.random.binomial(n = 1, size = (sprite_sizes[i],sprite_sizes[i]), p = 0.8)*order[i]\n",
+      "                sprites.append(sprite)\n",
+      "                x = self.a.add_sprite(input_grid = x, sprite = sprite)\n",
+      "            y = x.copy()\n",
+      "            for color in order:\n",
+      "                x[x==color] = 5\n",
+      "            x = np.concatenate((x,order_rows))\n",
+      "            return x,y\n",
+      "        \n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for task,task_dict in ordering_dict.items():\n",
+    "    scm_name = task.split(\"!\")[0]\n",
+    "    scm = task_dict[\"scm\"].replace(\"get_xy\", scm_name)\n",
+    "    scm = scm.replace(\"\\n        def\", \"def\")\n",
+    "    scm = scm.replace(\"(colors):\", \"(colors: list):\")\n",
+    "    task_dict[\"scm\"] = scm\n",
+    "    print(scm)\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "105df615-908d-4051-9979-118ee3e88305",
+   "metadata": {},
+   "source": [
+    "# Logical"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "a38acd71-7174-4813-aec7-57c5889ce219",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SCMdky5!or10x10\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_or(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!or15x15\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_or(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!or20x20\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_or(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMtcbq!xor!or!4x4\n",
+      "\n",
+      "        def get_xy(upper: np.array = None, middle: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if middle is None:\n",
+      "                middle = np.random.choice([0,middle_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "            # Get x.\n",
+      "            x = np.concatenate((upper,middle,lower), axis = 0).astype(int)\n",
+      "            # Get y.\n",
+      "            y = fun_0(upper,middle).astype(int)\n",
+      "            y = fun_1(y,lower).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,middle,lower)\n",
+      "        \n",
+      "SCMtcbq!xor!or!8x8\n",
+      "\n",
+      "        def get_xy(upper: np.array = None, middle: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if middle is None:\n",
+      "                middle = np.random.choice([0,middle_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "            # Get x.\n",
+      "            x = np.concatenate((upper,middle,lower), axis = 0).astype(int)\n",
+      "            # Get y.\n",
+      "            y = fun_0(upper,middle).astype(int)\n",
+      "            y = fun_1(y,lower).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,middle,lower)\n",
+      "        \n",
+      "SCMtcbq!or!and!4x4\n",
+      "\n",
+      "        def get_xy(upper: np.array = None, middle: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if middle is None:\n",
+      "                middle = np.random.choice([0,middle_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "            # Get x.\n",
+      "            x = np.concatenate((upper,middle,lower), axis = 0).astype(int)\n",
+      "            # Get y.\n",
+      "            y = fun_0(upper,middle).astype(int)\n",
+      "            y = fun_1(y,lower).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,middle,lower)\n",
+      "        \n",
+      "SCMtcbq!or!and!8x8\n",
+      "\n",
+      "        def get_xy(upper: np.array = None, middle: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if middle is None:\n",
+      "                middle = np.random.choice([0,middle_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "            # Get x.\n",
+      "            x = np.concatenate((upper,middle,lower), axis = 0).astype(int)\n",
+      "            # Get y.\n",
+      "            y = fun_0(upper,middle).astype(int)\n",
+      "            y = fun_1(y,lower).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,middle,lower)\n",
+      "        \n",
+      "SCMu3am!and!xor!axis0!4x4\n",
+      "\n",
+      "        def get_xy(upper: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "\n",
+      "            # Get x and y.\n",
+      "            x = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "            y = np.zeros(size).astype(int)\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if alternate_axis:\n",
+      "                        if j % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "                    else:\n",
+      "                        if i % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,lower)\n",
+      "        \n",
+      "SCMu3am!and!xor!axis0!8x8\n",
+      "\n",
+      "        def get_xy(upper: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "\n",
+      "            # Get x and y.\n",
+      "            x = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "            y = np.zeros(size).astype(int)\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if alternate_axis:\n",
+      "                        if j % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "                    else:\n",
+      "                        if i % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,lower)\n",
+      "        \n",
+      "SCMu3am!xor!or!axis1!4x4\n",
+      "\n",
+      "        def get_xy(upper: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "\n",
+      "            # Get x and y.\n",
+      "            x = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "            y = np.zeros(size).astype(int)\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if alternate_axis:\n",
+      "                        if j % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "                    else:\n",
+      "                        if i % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,lower)\n",
+      "        \n",
+      "SCMu3am!xor!or!axis1!8x8\n",
+      "\n",
+      "        def get_xy(upper: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "\n",
+      "            # Get x and y.\n",
+      "            x = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "            y = np.zeros(size).astype(int)\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if alternate_axis:\n",
+      "                        if j % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "                    else:\n",
+      "                        if i % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,lower)\n",
+      "        \n",
+      "SCMdky5!and25x25\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_and(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!or25x25\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_or(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!xor25x25\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_xor(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!xor10x10\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_xor(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!xor15x15\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_xor(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!xor20x20\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_xor(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!and10x10\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_and(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!and15x15\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_and(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "SCMdky5!and20x20\n",
+      "def get_xy(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_and(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Consolidate.\n",
+    "all_logical_dict = dict()\n",
+    "\n",
+    "# Rename tasks.\n",
+    "for d in logical_dicts:\n",
+    "    for task,task_dict in d.items():\n",
+    "        if \"SCMdky5\" in task:\n",
+    "            task_name = task.replace(\"SCMdky5\", \"SCMdky5!\")\n",
+    "        else:\n",
+    "            task_name = task\n",
+    "        all_logical_dict[task_name] = task_dict\n",
+    "        print(task_name)\n",
+    "        print(task_dict[\"scm\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "ad661853-a0aa-4733-8a63-ddef98179cf1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_or(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_or(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_or(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMtcbq\n",
+      "def SCMtcbq(upper: np.array = None, middle: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if middle is None:\n",
+      "                middle = np.random.choice([0,middle_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "            # Get x.\n",
+      "            x = np.concatenate((upper,middle,lower), axis = 0).astype(int)\n",
+      "            # Get y.\n",
+      "            y = fun_0(upper,middle).astype(int)\n",
+      "            y = fun_1(y,lower).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,middle,lower)\n",
+      "        \n",
+      "\n",
+      "SCMtcbq\n",
+      "def SCMtcbq(upper: np.array = None, middle: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if middle is None:\n",
+      "                middle = np.random.choice([0,middle_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "            # Get x.\n",
+      "            x = np.concatenate((upper,middle,lower), axis = 0).astype(int)\n",
+      "            # Get y.\n",
+      "            y = fun_0(upper,middle).astype(int)\n",
+      "            y = fun_1(y,lower).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,middle,lower)\n",
+      "        \n",
+      "\n",
+      "SCMtcbq\n",
+      "def SCMtcbq(upper: np.array = None, middle: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if middle is None:\n",
+      "                middle = np.random.choice([0,middle_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "            # Get x.\n",
+      "            x = np.concatenate((upper,middle,lower), axis = 0).astype(int)\n",
+      "            # Get y.\n",
+      "            y = fun_0(upper,middle).astype(int)\n",
+      "            y = fun_1(y,lower).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,middle,lower)\n",
+      "        \n",
+      "\n",
+      "SCMtcbq\n",
+      "def SCMtcbq(upper: np.array = None, middle: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if middle is None:\n",
+      "                middle = np.random.choice([0,middle_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "            # Get x.\n",
+      "            x = np.concatenate((upper,middle,lower), axis = 0).astype(int)\n",
+      "            # Get y.\n",
+      "            y = fun_0(upper,middle).astype(int)\n",
+      "            y = fun_1(y,lower).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,middle,lower)\n",
+      "        \n",
+      "\n",
+      "SCMu3am\n",
+      "def SCMu3am(upper: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "\n",
+      "            # Get x and y.\n",
+      "            x = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "            y = np.zeros(size).astype(int)\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if alternate_axis:\n",
+      "                        if j % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "                    else:\n",
+      "                        if i % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,lower)\n",
+      "        \n",
+      "\n",
+      "SCMu3am\n",
+      "def SCMu3am(upper: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "\n",
+      "            # Get x and y.\n",
+      "            x = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "            y = np.zeros(size).astype(int)\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if alternate_axis:\n",
+      "                        if j % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "                    else:\n",
+      "                        if i % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,lower)\n",
+      "        \n",
+      "\n",
+      "SCMu3am\n",
+      "def SCMu3am(upper: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "\n",
+      "            # Get x and y.\n",
+      "            x = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "            y = np.zeros(size).astype(int)\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if alternate_axis:\n",
+      "                        if j % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "                    else:\n",
+      "                        if i % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,lower)\n",
+      "        \n",
+      "\n",
+      "SCMu3am\n",
+      "def SCMu3am(upper: np.array = None, lower: np.array = None):\n",
+      "            # Used when there is no intervention.\n",
+      "            if upper is None:\n",
+      "                upper = np.random.choice([0,upper_color], size = size)\n",
+      "            if lower is None:\n",
+      "                lower = np.random.choice([0,lower_color], size = size)\n",
+      "\n",
+      "            # Get x and y.\n",
+      "            x = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "            y = np.zeros(size).astype(int)\n",
+      "            for i in range(y.shape[0]):\n",
+      "                for j in range(y.shape[1]):\n",
+      "                    if alternate_axis:\n",
+      "                        if j % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "                    else:\n",
+      "                        if i % 2 == 0:\n",
+      "                            y[i,j] = fun_0(upper[i,j],lower[i,j]).astype(int)\n",
+      "                        else:\n",
+      "                            y[i,j] = fun_1(upper[i,j],lower[i,j]).astype(int)\n",
+      "            y *= output_color\n",
+      "            return x,y,(upper,lower)\n",
+      "        \n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_and(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_or(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_xor(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_xor(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_xor(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_xor(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_and(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_and(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n",
+      "SCMdky5\n",
+      "def SCMdky5(upper_color,lower_color,output_color,size):\n",
+      "\tupper = np.random.choice([0,upper_color], size = size)\n",
+      "\tlower = np.random.choice([0,lower_color], size = size)\n",
+      "\tx = np.concatenate((upper,lower), axis = 0).astype(int)\n",
+      "\ty = np.logical_and(upper,lower).astype(int)\n",
+      "\ty *= output_color\n",
+      "\treturn x,y\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Update SCMs.\n",
+    "for task,task_dict in all_logical_dict.items():\n",
+    "    scm_name = task.split(\"!\")[0]\n",
+    "    print(scm_name)\n",
+    "    scm = task_dict[\"scm\"].replace(\"get_xy\", scm_name)\n",
+    "    scm = scm.replace(\"\\n        def\", \"def\")\n",
+    "    scm = scm.replace(\"(colors):\", \"(colors: list):\")\n",
+    "    task_dict[\"scm\"] = scm\n",
+    "    print(scm)\n",
+    "    print()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "952db1ff-2129-467c-a51a-c4b701d5f45f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "20"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(all_logical_dict.keys())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "f8cd20d7-fc19-4937-93fc-9b1f0ab40fc7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['SCMdky5!or10x10', 'SCMdky5!or15x15', 'SCMdky5!or20x20', 'SCMtcbq!xor!or!4x4', 'SCMtcbq!xor!or!8x8', 'SCMtcbq!or!and!4x4', 'SCMtcbq!or!and!8x8', 'SCMu3am!and!xor!axis0!4x4', 'SCMu3am!and!xor!axis0!8x8', 'SCMu3am!xor!or!axis1!4x4', 'SCMu3am!xor!or!axis1!8x8', 'SCMdky5!and25x25', 'SCMdky5!or25x25', 'SCMdky5!xor25x25', 'SCMdky5!xor10x10', 'SCMdky5!xor15x15', 'SCMdky5!xor20x20', 'SCMdky5!and10x10', 'SCMdky5!and15x15', 'SCMdky5!and20x20'])"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_logical_dict.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "7cdad951-5e03-4958-aa2b-e59943381f38",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['scm', 'latex', 'test', 'parent_to_children_dict', 'directed_adjacency_matrix', 'train'])"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_logical_dict[\"SCMdky5!or10x10\"].keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "42dcc008-b868-4546-bff8-a53e86ebc4fe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict_keys(['input', 'output'])"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "all_logical_dict[\"SCMdky5!or10x10\"][\"test\"][0].keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "124bc679-9326-42e3-946f-f063699905a0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/Users/jmaasch/Desktop/cornell/causal_arc/data/static_evaluation_set/v0_09-01-25\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pwd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "85eb7f27-0001-4e5d-8576-a88157674401",
+   "metadata": {},
+   "source": [
+    "# Export"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "a992a9fe-70c9-4649-918c-dbf7fce67f4b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Export tasks.\n",
+    "with open(\"processed/causal_arc_logical.json\", \"w\") as f:\n",
+    "    json.dump(all_logical_dict, f, indent = 4) # indent for readability.\n",
+    "\n",
+    "# Export solutions file.\n",
+    "logical_solutions = dict()\n",
+    "for task,d in all_logical_dict.items():\n",
+    "    test_output = d[\"test\"][0].get(\"output\")\n",
+    "    logical_solutions[task] = [test_output]\n",
+    "with open('processed/causal_arc_logical_solutions.json', 'w') as f:\n",
+    "    json.dump(logical_solutions, f, indent = 4) # indent for readability."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "d64367b8-660d-4b77-9f7c-176a02d3c6ae",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "20"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(logical_solutions.keys())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "d220fcbc-7cd9-4b58-86df-9b06f065af92",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Export tasks.\n",
+    "with open(\"processed/causal_arc_counting.json\", \"w\") as f:\n",
+    "    json.dump(counting_dict, f, indent = 4) # indent for readability."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "44a40f70-bc74-4d13-9dd5-bb07682f3f00",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Export tasks.\n",
+    "with open(\"processed/causal_arc_extension.json\", \"w\") as f:\n",
+    "    json.dump(extension_dict, f, indent = 4) # indent for readability."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "fe2f7af0-62bc-4fc3-9beb-7cda0e11adf7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Export tasks.\n",
+    "with open(\"processed/causal_arc_ordering.json\", \"w\") as f:\n",
+    "    json.dump(ordering_dict, f, indent = 4) # indent for readability."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aa60c0b1-5c10-4371-a944-31cd4407b86a",
+   "metadata": {},
+   "source": [
+    "# End of document"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5eb51244-151f-4ee0-a3db-cd4cc05c87c0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "hf",
+   "language": "python",
+   "name": "hf"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

static_evaluation_set/v0_09-01-25/counting/causal_arc_counting_solutions.json

@@ -0,0 +1 @@
+{"SCMm5ob_10x10": [[[2, 0, 0, 0], [2, 0, 0, 1], [2, 0, 0, 1], [2, 0, 4, 1], [2, 0, 4, 1], [2, 0, 4, 1], [2, 7, 4, 1], [2, 7, 4, 1]]], "SCMm5ob_15x15": [[[0, 2, 0, 0], [0, 2, 0, 0], [7, 2, 0, 0], [7, 2, 0, 0], [7, 2, 0, 0], [7, 2, 0, 1], [7, 2, 9, 1], [7, 2, 9, 1], [7, 2, 9, 1], [7, 2, 9, 1], [7, 2, 9, 1], [7, 2, 9, 1], [7, 2, 9, 1], [7, 2, 9, 1], [7, 2, 9, 1]]], "SCMm5ob_20x20": [[[1, 0, 2, 0], [1, 0, 2, 0], [1, 0, 2, 0], [1, 0, 2, 0], [1, 0, 2, 0], [1, 0, 2, 0], [1, 3, 2, 0], [1, 3, 2, 0], [1, 3, 2, 0], [1, 3, 2, 0], [1, 3, 2, 0], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9], [1, 3, 2, 9]]], "SCMev5t_10x10": [[[4, 0], [5, 0], [1, 1]]], "SCMev5t_15x15": [[[5, 0, 0], [7, 7, 0], [2, 2, 2]]], "SCMev5t_20x20": [[[8, 0], [1, 1], [4, 4]]], "SCMfuy3": [[[0.0, 0.0, 0.0], [0.0, 8.0, 0.0], [0.0, 0.0, 0.0], [4.0, 4.0, 4.0], [4.0, 4.0, 4.0], [4.0, 4.0, 4.0], [4.0, 4.0, 4.0], [4.0, 4.0, 4.0], [4.0, 4.0, 4.0], [0.0, 0.0, 0.0], [0.0, 6.0, 0.0], [0.0, 0.0, 0.0]]], "SCMhlh2": [[[7, 7, 7]]], "SCM43rz": [[[1]]], "SCM95ls": [[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 8, 8, 8, 8, 0, 0], [0, 0, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 8, 8, 0, 0, 0, 0, 0, 0], [0, 0, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 8, 8, 8, 8, 8, 8, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]]}

static_evaluation_set/v0_09-01-25/extension/causal_arc_extension.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c1f00e2621b49427a428fa04440844ce1af46652146b3c4c0fbdda049f73e45
+size 15588671

static_evaluation_set/v0_09-01-25/extension/causal_arc_extension_solutions.json

@@ -0,0 +1 @@
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static_evaluation_set/v0_09-01-25/ordering/causal_arc_ordering_solutions.json

@@ -0,0 +1 @@
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