remove tools folder

tools/testing_util.py

@@ -1,438 +0,0 @@
-import json
-import sys
-import faulthandler
-
-# used for debugging to time steps
-from datetime import datetime
-
-# to run the solution files we're using a timing based approach
-import signal
-
-import numpy as np
-# for capturing the stdout
-from io import StringIO
-# used for testing the code that reads from input
-from unittest.mock import patch, mock_open
-
-from pyext import RuntimeModule
-
-from enum import Enum
-class CODE_TYPE(Enum):
-    call_based = 0
-    standard_input = 1
-
-# stuff for setting up signal timer
-class TimeoutException(Exception):
-    pass
-def timeout_handler(signum, frame):
-    print("alarm went off")
-    #return
-    raise TimeoutException
-signal.signal(signal.SIGALRM, timeout_handler)
-timeout = 4  # seconds
-
-# used to capture stdout as a list
-# from https://stackoverflow.com/a/16571630/6416660
-# alternative use redirect_stdout() from contextlib
-class Capturing(list):
-    def __enter__(self):
-        self._stdout = sys.stdout
-        sys.stdout = self._stringio = StringIO()
-        # Make closing the StringIO a no-op
-        self._stringio.close = lambda x: 1
-        return self
-    def __exit__(self, *args):
-        self.extend(self._stringio.getvalue().splitlines())
-        del self._stringio    # free up some memory
-        sys.stdout = self._stdout
-
-
-def run_test(sample, test=None, debug=False):
-    """
-    if test(generated_code) is not None it'll try to run the code.
-    otherwise it'll just return an input and output pair.
-    """
-    if debug:
-        print(f"start = {datetime.now().time()}")
-
-    try:
-        in_outs = json.loads(sample["input_output"])
-    except ValueError:
-        in_outs = None
-    if in_outs:
-        if in_outs.get("fn_name") is None:
-            which_type = CODE_TYPE.standard_input  # Standard input
-            method_name = None
-        else:
-            which_type = CODE_TYPE.call_based  # Call-based
-            method_name = in_outs["fn_name"]
-
-    if debug:
-        print(f"loaded input_output = {datetime.now().time()}")
- 
-    if test is None:
-        return in_outs
-    elif test is not None:
-        results = []
-        sol = "import sys\nimport time\nimport itertools\nfrom itertools import accumulate, product, permutations, combinations\nimport collections\nfrom collections import Counter, OrderedDict, deque, defaultdict, ChainMap\nfrom functools import lru_cache\nimport math\nfrom math import sqrt, sin, cos, tan, ceil, fabs, floor, gcd, exp, log, log2\nimport fractions\nfrom typing import List, Tuple\nimport numpy as np\nimport random\nimport heapq\nfrom heapq import *\n"
-        if debug:
-            print(f"loading test code = {datetime.now().time()}")
- 
-        if which_type == CODE_TYPE.call_based:
-            sol += test
-            if debug:
-                print(f"sol = {sol}")
-            signal.alarm(timeout)
-            try:
-                tmp_sol = RuntimeModule.from_string("tmp_sol", "", sol)
-                if "class Solution" not in test:
-                    tmp = tmp_sol
-                else:
-                    tmp = tmp_sol.Solution()
-                signal.alarm(0)
-            except Exception as e:
-                signal.alarm(0)
-                if debug:
-                     print(f"type 0 compilation error = {e}")
-                results.append(-2)
-                return results
-            signal.alarm(0)
-
-        elif which_type == CODE_TYPE.standard_input:
-            # sol
-            tmp_test = test.split("\n")
-
-            new_test = []
-            for x in tmp_test:
-                if (not x.startswith("from ")) and (not x.startswith("import ")):
-                    new_test.append("\t" + x + "\n")
-                else:
-                    new_test.append(x + "\n")
-            tmp_test = new_test
-            
-            new_test = ""
-            started = False
-            for i in tmp_test:
-                if i.startswith("\t") and not started:
-                    new_test += "stdin = sys.stdin\nstdout = sys.stdout\n"
-                    new_test += "def code():\n"
-                    new_test += i
-                    started = True
-                elif started and ((i.startswith("from ")) or (i.startswith("import "))): 
-                    new_test += "\t" + i
-                else:
-                    new_test += i
-            tmp_test = new_test
-
-            sol += tmp_test
-            if debug:
-                print(f"sol = {sol}")
-            method_name = "code"
-            signal.alarm(timeout)
-            try:
-                tmp_sol = RuntimeModule.from_string("tmp_sol", "", sol)
-                tmp = tmp_sol
-                signal.alarm(0)
-            except Exception as e:
-                signal.alarm(0)
-                if debug:
-                    print(f"type 1 compilation error = {e}")
-                results.append(-2)
-                return results
-            signal.alarm(0)
-        if debug:
-            print(f"get method = {datetime.now().time()}")
- 
-        try:
-            method = getattr(tmp, method_name)  # get_attr second arg must be str
-        except:
-            signal.alarm(0)
-            e = sys.exc_info()
-            print(f"unable to get function error = {e}")
-            return results
-
-        for index, inputs in enumerate(in_outs["inputs"]):
-            # JSON forces dictionaries to have string keys; this undoes this (assuming a singleton list)
-            try:
-                if isinstance(inputs[0], dict):
-                    inputs = [{int(k): v for k,v in inputs[0].items()}]
-            except:
-                True
-            try:
-                if isinstance(in_outs["outputs"][index], dict):
-                    in_outs["outputs"][index] = [{int(k): v for k,v in in_outs["outputs"][index].items()}]
-            except:
-                True
-            try:
-                if isinstance(in_outs["outputs"][index][0], dict):
-                    in_outs["outputs"][index] = [{int(k): v for k,v in in_outs["outputs"][index][0].items()}]
-            except:
-                True
-
-            if debug:
-                print(f"time: {datetime.now().time()} testing index = {index}  inputs = {inputs}, {type(inputs)}. type = {which_type}")
-            if which_type == CODE_TYPE.call_based:  # Call-based
-                signal.alarm(timeout)
-                faulthandler.enable()
-                try:
-                    output = method(*inputs)
-
-                    # ground truth sequences are not tuples
-                    if isinstance(output, tuple):
-                        output = list(output)
-                    
-                    tmp_result = output == in_outs["outputs"][index]
-                    if isinstance(in_outs["outputs"][index], list) and in_outs["outputs"][index]:
-                        tmp_result = tmp_result or (output == in_outs["outputs"][index][0])
-
-                    # ground truth sequences are not tuples
-                    try:
-                        if isinstance(output[0], tuple):
-                            tmp_result = tmp_result or ([list(x) for x in output] == in_outs["outputs"][index][0])
-                    except:
-                        True
-                    results.append(tmp_result)
-
-                    # reset the alarm
-                    signal.alarm(0)
-                except Exception as e:
-                    signal.alarm(0)
-                    faulthandler.disable()
-                    print(f"Standard input runtime error or time limit exceeded error = {e}")
-                    results.append(-1)
-                    continue
-                faulthandler.disable()
-                signal.alarm(0)
-                if debug:
-                    print(f"outputs = {output}, test outputs = {in_outs['outputs'][index]}, inputs = {inputs}, {type(inputs)}, {output == [in_outs['outputs'][index]]}")
-            elif which_type == CODE_TYPE.standard_input:  # Standard input
-                faulthandler.enable()
-                signal.alarm(timeout)
-                passed = False
-
-                if isinstance(inputs, list):
-                    inputs = "\n".join(inputs)
-                if isinstance(in_outs['outputs'][index], list):
-                    in_outs['outputs'][index] = "\n".join(in_outs['outputs'][index])
-
-                with Capturing() as output:
-                    try:
-                        call_method(method, inputs)
-                        # reset the alarm
-                        signal.alarm(0)
-                        passed = True
-                    except Exception as e:
-                        # runtime error or took too long
-                        signal.alarm(0)
-                        print(f"Call-based runtime error or time limit exceeded error = {repr(e)}{e}")
-                        results.append(-1)
-                    signal.alarm(0)
-
-                if not passed:
-                    if debug:
-                        nl = "\n"
-                        if not isinstance(inputs, list):
-                            print(f"not passed output = {output}, test outputs = {in_outs['outputs'][index]}, inputs = {inputs.replace(nl,' new-line ')}, {type(inputs)}, {output == [in_outs['outputs'][index]]}")
-                        else:
-                            print(f"not passed output = {output}, test outputs = {in_outs['outputs'][index]}, inputs = {inputs}, {type(inputs)}, {output == [in_outs['outputs'][index]]}")
-                    continue
-
-                if passed and debug:
-                    print(f"==> output = {output}, test outputs = {in_outs['outputs'][index]}")
-
-                if custom_compare_(output, in_outs['outputs'][index]):
-                    tmp_result = True
-                    results.append(tmp_result)
-                    continue
-
-                # ground truth sequences are expressed as lists not tuples
-                if isinstance(output, tuple):
-                    output = list(output)
-
-                tmp_result = False
-                try:
-                    tmp_result = (output == [in_outs["outputs"][index]])
-                    if isinstance(in_outs["outputs"][index], list):
-                        tmp_result = tmp_result or (output == in_outs["outputs"][index])
-                        if isinstance(output[0], str):
-                            tmp_result = tmp_result or ([e.strip() for e in output] == in_outs["outputs"][index])
-                except Exception as e:
-                    if debug:
-                        print(f"Failed check1 exception = {e}")
-                    pass
-
-                if tmp_result == True:  
-                    results.append(tmp_result)
-                    continue
-
-                # try one more time without \n
-                if isinstance(in_outs["outputs"][index], list):
-                    for tmp_index, i in enumerate(in_outs["outputs"][index]):
-                        in_outs["outputs"][index][tmp_index] = i.split("\n")
-                        in_outs["outputs"][index][tmp_index] = [x.strip() for x in in_outs["outputs"][index][tmp_index] if x]
-                else:
-                    in_outs["outputs"][index] = in_outs["outputs"][index].split("\n")
-                    in_outs["outputs"][index] = list(filter(len, in_outs["outputs"][index]))
-                    in_outs["outputs"][index] = list(map(lambda x:x.strip(), in_outs["outputs"][index]))
-
-                try:
-                    tmp_result = (output == [in_outs["outputs"][index]])
-                    if isinstance(in_outs["outputs"][index], list):
-                        tmp_result = tmp_result or (output == in_outs["outputs"][index])
-                except Exception as e:
-                    if debug:
-                        print(f"Failed check2 exception = {e}")
-                    pass
-
-                if tmp_result == True:
-                    results.append(tmp_result)
-                    continue
-
-                # try by converting the output into a split up list too
-                if isinstance(output, list):
-                    output = list(filter(len, output))
-
-                if debug:
-                    nl = "\n"
-                    if not isinstance(inputs, list):
-                        print(f"output = {output}, test outputs = {in_outs['outputs'][index]}, inputs = {inputs.replace(nl,' new-line ')}, {type(inputs)}, {output == [in_outs['outputs'][index]]}") 
-                    else:
-                        print(f"output = {output}, test outputs = {in_outs['outputs'][index]}, inputs = {inputs}, {type(inputs)}, {output == [in_outs['outputs'][index]]}") 
-                
-                if tmp_result == True:
-                    results.append(tmp_result)
-                    continue
-
-                try:
-                    tmp_result = (output == [in_outs["outputs"][index]])
-                    if isinstance(in_outs["outputs"][index], list):
-                        tmp_result = tmp_result or (output == in_outs["outputs"][index])
-                except Exception as e:
-                    if debug:
-                        print(f"Failed check3 exception = {e}")
-                    pass
-
-                try:
-                    output_float = [float(e) for e in output]
-                    gt_float = [float(e) for e in in_outs['outputs'][index]]
-                    tmp_result = tmp_result or ((len(output_float) == len(gt_float)) and np.allclose(output_float, gt_float))
-                except Exception as e:
-                    pass
-                try:
-                    if isinstance(output[0], list):
-                        output_float = [float(e) for e in output[0]]
-                        gt_float = [float(e) for e in in_outs['outputs'][index][0]]
-                        tmp_result = tmp_result or ((len(output_float) == len(gt_float)) and np.allclose(output_float, gt_float))
-                except Exception as e:
-                    pass
-
-                if tmp_result == True:
-                    results.append(tmp_result)
-                    continue
-
-                # try by converting the stuff into split up list
-                if isinstance(in_outs["outputs"][index], list):
-                    for tmp_index, i in enumerate(in_outs["outputs"][index]):
-                        in_outs["outputs"][index][tmp_index] = set(i.split())
-                else:
-                    in_outs["outputs"][index] = set(in_outs["outputs"][index].split())
-
-                try:
-                    tmp_result = (output == in_outs["outputs"][index])
-                except Exception as e:
-                    if debug:
-                        print(f"Failed check4 exception = {e}")
-                    continue
-
-                if tmp_result == True:
-                    results.append(tmp_result)
-                    continue 
-
-                # try by converting the output into a split up list too
-                if isinstance(output, list):
-                    for tmp_index, i in enumerate(output):
-                        output[tmp_index] = i.split()
-                    output = list(filter(len, output))
-                    for tmp_index, i in enumerate(output):
-                        output[tmp_index] = set(i)    
-                else:
-                    output = output.split()
-                    output = list(filter(len, output))
-                    output = set(output)
-
-                try:
-                    tmp_result = (set(frozenset(s) for s in output) == set(frozenset(s) for s in in_outs["outputs"][index]))
-                except Exception as e:
-                    if debug:
-                        print(f"Failed check5 exception = {e}")
-
-
-                # if they are all numbers, round so that similar numbers are treated as identical
-                try:
-                    tmp_result = tmp_result or (set(frozenset(round(float(t),3) for t in s) for s in output) ==\
-                        set(frozenset(round(float(t),3) for t in s) for s in in_outs["outputs"][index]))
-                except Exception as e:
-                    if debug:
-                        print(f"Failed check6 exception = {e}")
-                
-                if tmp_result == True and debug:
-                    print("PASSED")
- 
-                results.append(tmp_result)
-                
-                if debug:
-                    nl = "\n"
-                    if not isinstance(inputs, list):
-                        print(f"output = {output}, test outputs = {in_outs['outputs'][index]}, inputs = {inputs.replace(nl,' new-line ')}, {type(inputs)}, {output == [in_outs['outputs'][index]]}")
-                    else:
-                        print(f"output = {output}, test outputs = {in_outs['outputs'][index]}, inputs = {inputs}, {type(inputs)}, {output == [in_outs['outputs'][index]]}") 
-
-
-    return results
-
-
-def custom_compare_(output, ground_truth):
-    
-    if isinstance(output, list):
-        output_1 = "\n".join(output)
-        if stripped_string_compare(output_1, ground_truth):
-            return True
-
-    if isinstance(output, list):
-        output_2 = [o.lstrip().rstrip() for o in output]
-        output_2 = "\n".join(output_2)
-        if stripped_string_compare(output_2, ground_truth):
-            return True
-
-    return False
-
-def stripped_string_compare(s1, s2):
-    s1 = s1.lstrip().rstrip()
-    s2 = s2.lstrip().rstrip()
-    return s1 == s2
-
-def call_method(method, inputs):
-
-    if isinstance(inputs, list):
-        inputs = "\n".join(inputs)
-
-    inputs_line_iterator = iter(inputs.split("\n"))
-
-    # sys.setrecursionlimit(10000)
-
-    # @patch('builtins.input', side_effect=inputs.split("\n"))
-    @patch('builtins.open', mock_open(read_data=inputs))
-    @patch('sys.stdin', StringIO(inputs))
-    @patch('sys.stdin.readline', lambda *args: next(inputs_line_iterator))
-    @patch('sys.stdin.readlines', lambda *args: inputs.split("\n"))
-    @patch('sys.stdin.read', lambda *args: inputs)
-    # @patch('sys.stdout.write', print)
-    def _inner_call_method(_method):
-        try:
-            return _method()
-        except SystemExit as e:
-            pass
-        finally:
-            pass
-    return _inner_call_method(method) 
-

tools/utils.py

@@ -1,188 +0,0 @@
-import itertools
-import numpy as np
-from typing import Dict
-from datasets import load_dataset
-import tools.testing_util as test_util
-
-
-DATASET = "codeparrot/apps"
-
-
-def evaluate_generations(generations: list, level: str = "all", debug: bool = False):
-    """We take the list of code generations and try to compile them
-     and the run their corresponding unit tests which are retrieved from the APPS dataset.
-
-    Args:
-        generations: list of code generations (same order as samples in APPS dataset)
-        level: difficulty level used in the generation, can be "all", "introductory", "interview" or "competition"
-
-    Returns:
-        results: dictionary of results, key is the problem index, value is a list of results for each generation
-        [-2] = compile error, [-1] = runtime error [False] = failed test case [True] = passed test case
-     """
-
-    # generations are code generations in the same order of the dataset
-    apps_eval = load_dataset(DATASET, split="test", difficulties=[level])
-    results = {}
-    for index in range(len(generations)):
-        # code generations for problem (index)
-        problem_generations = generations[index]
-        # get corresponding samples from APPS dataset
-        sample = apps_eval[index]
-        res = []
-        # loop over the generations
-        for o_idx, o in enumerate(problem_generations):
-            curr_res = [-2]
-            try:
-                curr_res = test_util.run_test(sample, test=o, debug=debug)
-                #if debug:
-                print(f"\nSuccessful compilation of task {index}!")
-                fixed = []
-                for e in curr_res:
-                    if isinstance(e, np.ndarray):
-                       e = e.item(0)
-                    if isinstance(e, np.bool_):
-                        e = bool(e)
-                    fixed.append(e)
-                curr_res = fixed
-                if not np.all(curr_res):
-                    #if debug:
-                    print(f"Results were not True for all test cases")
-            except Exception as e:
-                if debug:
-                    print(f"Compilation failed, test framework exception = {repr(e)}{e}\n")
-                break
-            finally:
-                assert isinstance(curr_res, list)
-                res.append(curr_res)
-        results[index] = res
-    return results
-
-
-def estimate_pass_at_k(num_samples, num_correct, k):
-    """Estimates pass@k of each problem and returns them in an array."""
-
-    def estimator(n: int, c: int, k: int) -> float:
-        """Calculates 1 - comb(n - c, k) / comb(n, k)."""
-        if n - c < k:
-            return 1.0
-        return 1.0 - np.prod(1.0 - k / np.arange(n - c + 1, n + 1))
-
-    if isinstance(num_samples, int):
-        num_samples_it = itertools.repeat(num_samples, len(num_correct))
-    else:
-        assert len(num_samples) == len(num_correct)
-        num_samples_it = iter(num_samples)
-
-    return np.array([estimator(int(n), int(c), k) for n, c in zip(num_samples_it, num_correct)])
-
-
-def get_results(results: Dict[int, list], count_errors: bool = False, k_list: list = [1, 10, 100]):
-    """
-    Given the results evaluated against the testcases we output some statistics.
-    For single generations:
-    >>> example_results = {0: [[-2]], 1: [[False,False]], 2: [[True,True]], 3: [[False,True,False,True]], 4: [[-1,-1]]}
-    >>> get_results(example_results, count_errors=True)
-    Computing accuracy metrics...
-    number of compile errors = 1 avg = 0.2
-    number of runtime errors = 1 avg = 0.2
-    number of problems evaluated = 5
-    Average Accuracy : 0.3
-    Strict Accuracy : 0.2
-    {'avg_accuracy': 0.3, 'strict_accuracy': 0.2, 'pass_at_k': None}
-
-    For multiple generations:
-    >>> example_results = {0: [[-2], [True, True, True]], 1: [[-1,-1, -1], [True, False, True]]}
-    >>> get_results(example_results, k_list=[1, 2])
-    Computing pass@k metric for multiple generations...
-    {'pass@1': 0.25, 'pass@2': 0.5}
-    {'avg_accuracy': None, 'strict_accuracy': None, 'pass_at_k': {'pass@1': 0.25, 'pass@2': 0.5}}
-    """
-
-    metrics = {"avg_accuracy": None, "strict_accuracy": None, "pass_at_k": None}
-
-    if len(results[0]) == 1:
-        # for single generations we compute average accuracy and stric accuracy: original APPS metrics
-        print("Computing accuracy metrics...")
-        res = []
-        per_prob_res = []
-        all_correct = []
-        for index in results:
-            problem_results = np.asarray(results[index])
-            res.extend(problem_results)
-            per_prob_res.append(np.mean(problem_results > 0))
-            all_correct.append(np.all(problem_results > 0))
-        # we count campilation and runtime errors once per pronlem
-        compile_errors = len([e for e in res if -2 in e])
-        runtime_errors = len([e for e in res if -1 in e])
-        total_testcases = len(res)
-        if count_errors:
-            print(f"number of compile errors = {compile_errors} avg = {compile_errors / total_testcases}")
-            print(f"number of runtime errors = {runtime_errors} avg = {runtime_errors / total_testcases}")
-            print(f"number of problems evaluated = {total_testcases}")
-
-        print(f"Average Accuracy : {np.mean(per_prob_res)}")
-        print(f"Strict Accuracy : {np.mean(all_correct)}")
-        metrics["avg_accuracy"] = np.mean(per_prob_res)
-        metrics["strict_accuracy"] = np.mean(all_correct)
-
-    else:
-        # for multiple generations we use pass@k metric used in the HumanEval benchmark
-        # we use strict accuracy, a generation is valid if it has to pass all the tests
-        print("Computing pass@k metric for multiple generations...")
-        # total is list with nb generations per task (task=index)
-        # correct is number of generations that passed all tests per task
-        total = []
-        correct = [] 
-        for index in results:
-            all_correct = []
-            for generation in results[index]:
-                gen = np.array(generation)
-                all_correct.append(np.all(gen>0))
-            total.append(len(all_correct))
-            correct.append(sum(all_correct))
-        total = np.array(total)
-        correct = np.array(correct)
-        ks = k_list
-        pass_at_k = {f"pass@{k}": estimate_pass_at_k(total, correct, k).mean() for k in ks if (total >= k).all()}
-        print(pass_at_k)
-        metrics["pass_at_k"] = pass_at_k
-    return metrics
-
-def compute_metrics(generations, level="all", k_list=[1, 10, 100], count_errors=True, debug=False):
-    """Return metrics for the given generations.
-    Args:
-        generations: list of code generations for each problem (each generation is a list of generations)
-        k_list: list of k values to compute pass@k when using multiple generations
-        count_errors: whether to count compilation and runtime errors when using single generations
-        level: difficulty level in APPS dataset that was used for the given generations (from: "all", "introductory", "interview", "competition")
-    Returns:
-        metrics: dict of metrics  
-
-    Examples:
-
-    >>> import json
-    >>> # lists of solutions to the two first APPS problems (note not all solutions pass all tests)
-    >>> solution_sample1 = json.load(open("test_examples/solutions_problem_1.json", "r"))
-    >>> solution_sample2 = json.load(open("test_examples/solutions_problem_2.json", "r"))
-    >>> single_solutions = [solution_sample1[:1], solution_sample2[:1]]
-    >>> compute_metrics(single_solutions, level="all")
-    Computing accuracy metrics...
-    number of compile errors = 0 avg = 0.0
-    number of runtime errors = 0 avg = 0.0
-    number of problems evaluated = 2
-    Average Accuracy : 1.0
-    Strict Accuracy : 1.0
-    {'avg_accuracy': 1.0, 'strict_accuracy': 1.0, 'pass_at_k': None}
-    >>> multiple_solutions = [solution_sample1[:3], solution_sample2[:3]]
-    >>> compute_metrics(multiple_solutions, level="all", k_list=[1, 2, 3])
-    Computing pass@k metric for multiple generations...
-    {'pass@1': 1.0, 'pass@2': 1.0, 'pass@3': 1.0}
-    {'avg_accuracy': None, 'strict_accuracy': None, 'pass_at_k': {'pass@1': 1.0, 'pass@2': 1.0, 'pass@3': 1.0}}
-    """
-    results = evaluate_generations(generations, level=level, debug=debug)
-    metrics = get_results(results, count_errors=count_errors, k_list=k_list)
-    return metrics
-
-#import doctest
-#doctest.testmod()