first commit

evaluate/count_resource.py

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+import json
+import pandas as pd
+from collections import defaultdict
+
+# Load the JSON file
+file_path = "solutions.json"
+with open(file_path, "r") as f:
+    data = json.load(f)
+
+# Initialize a dictionary to store the minimal LUT usage for each module and LLM
+lut_results = defaultdict(lambda: defaultdict(lambda: float("inf")))
+
+# Process the data to extract the minimum LUT usage per module per LLM
+for llm, categories in data.items():
+    for category, modules in categories.items():
+        for module_data in modules:
+            module_name = module_data["module"].replace("_", " ")  # Replace underscores with spaces
+            for solution in module_data.get("solutions", []):
+                if "resource usage" in solution and "optimized" in solution["resource usage"]:
+                    lut_count = solution["resource usage"]["optimized"].get("LUT", float("inf"))
+                    # Store the minimum LUT usage
+                    lut_results[module_name][llm] = min(lut_results[module_name][llm], lut_count)
+
+# Convert the dictionary into a DataFrame
+df_lut = pd.DataFrame.from_dict(lut_results, orient="index")
+
+# Save to a CSV file
+csv_output_path = "solution_resource_analysis.csv"
+df_lut.to_csv(csv_output_path)
+
+# Print the CSV file path
+print(f"CSV file saved at: {csv_output_path}")