def run_grader(part_id):
graded_funcs = {
"r9hUX": Test_tf_constant,
"kWeLo": Test_tf_square,
"E1weD": Test_tf_reshape,
"AuDvh": Test_tf_cast,
"NI9Co": Test_tf_multiply,
"Yz2KA": Test_tf_add,
"4uBzv": Test_tf_gradient_tape
}
g_func = graded_funcs.get(part_id)
if g_func is None:
print_stderr("The partID provided did not correspond to any graded function.")
return
failed_cases, num_cases = g_func()
score = 1.0 - len(failed_cases) / num_cases
if failed_cases:
failed_msg = ""
for failed_case in failed_cases:
failed_msg += f"Failed {failed_case.get('name')}.\nExpected:\n{failed_case.get('expected')},\nbut got:\n{failed_case.get('got')}.\n\n"
send_feedback(score, failed_msg)
else:
send_feedback(score, "All tests passed! Congratulations!")
def run_grader(part_id):
graded_funcs = {
"xV8vX": Test_distribute_datasets,
"dmTKR": Test_train_test_step_fns,
"cst37": Test_distributed_train_test_step_fns
}
g_func = graded_funcs.get(part_id)
if g_func is None:
print_stderr(
"The partID provided did not correspond to any graded function.")
return
try:
failed_cases, num_cases = g_func()
except:
traceback.print_exc()
send_feedback(
0.0,
"There was a problem grading your submission. Check stderr for more details."
)
exit()
score = 1.0 - len(failed_cases) / num_cases
if failed_cases:
failed_msg = ""
for failed_case in failed_cases:
failed_msg += f"Failed {failed_case.get('name')}.\nExpected:\n{failed_case.get('expected')},\nbut got:\n{failed_case.get('got')}.\n\n"
send_feedback(score, failed_msg)
else:
send_feedback(score, "All tests passed! Congratulations!")
def run_grader(part_id):
graded_funcs = {
"pxgPU": Test_map_fn,
"fX2cS": Test_set_adam_optimizer,
"M6COK": Test_set_sparse_cat_crossentropy_loss,
"fbLog": Test_set_sparse_cat_crossentropy_accuracy,
"FaW22": Test_prepare_dataset,
"C8oAS": Test_train_one_step,
"NG4Bn": Test_train
}
g_func = graded_funcs.get(part_id)
if g_func is None:
print_stderr(
"The partID provided did not correspond to any graded function.")
return
failed_cases, num_cases = g_func()
score = 1.0 - len(failed_cases) / num_cases
if failed_cases:
failed_msg = ""
for failed_case in failed_cases:
failed_msg += f"Failed {failed_case.get('name')}.\nExpected:\n{failed_case.get('expected')},\nbut got:\n{failed_case.get('got')}.\n\n"
send_feedback(score, failed_msg)
else:
send_feedback(score, "All tests passed! Congratulations!")
def run_grader(part_id):
graded_funcs = {
"mylyu": Test_F1ScoreResult,
"YQutN": Test_apply_gradients,
"8dNmL": Test_train_data_for_one_epoch
}
g_func = graded_funcs.get(part_id)
if g_func is None:
print_stderr("The partID provided did not correspond to any graded function.")
return
failed_cases, num_cases = g_func()
score = 1.0 - len(failed_cases) / num_cases
if failed_cases:
failed_msg = ""
for failed_case in failed_cases:
failed_msg += f"Failed {failed_case.get('name')}.\nExpected:\n{failed_case.get('expected')},\nbut got:\n{failed_case.get('got')}.\n\n"
send_feedback(score, failed_msg)
else:
send_feedback(score, "All tests passed! Congratulations!")
def cell_output_pattern_matching(cell, patterns):
if cell.get('cell_type') != 'code':
err_msg = "evaluated cell is not a code cell."
print_stderr(err_msg)
return False, err_msg
output_dict = cell.get('outputs')[0]
if output_dict.get('ename'):
return False, 'cell has errors.'
if output_dict.get('name'):
output_txt = output_dict.get('text')
for line in output_txt:
missing_patterns = [k for k, v in patterns.items() if not v]
for mp in missing_patterns:
if mp in line:
patterns.update({mp: True})
if not all(patterns.values()):
return False, "missing patterns."
return True, "passed!"
"mylyu": Test_F1ScoreResult,
"YQutN": Test_apply_gradients,
"8dNmL": Test_train_data_for_one_epoch
}
g_func = graded_funcs.get(part_id)
if g_func is None:
print_stderr("The partID provided did not correspond to any graded function.")
return
failed_cases, num_cases = g_func()
score = 1.0 - len(failed_cases) / num_cases
if failed_cases:
failed_msg = ""
for failed_case in failed_cases:
failed_msg += f"Failed {failed_case.get('name')}.\nExpected:\n{failed_case.get('expected')},\nbut got:\n{failed_case.get('got')}.\n\n"
send_feedback(score, failed_msg)
else:
send_feedback(score, "All tests passed! Congratulations!")
if __name__ == "__main__":
try:
part_id = sys.argv[2]
except IndexError:
print_stderr("Missing partId. Required to continue.")
send_feedback(0.0, "Missing partId.")
else:
run_grader(part_id)
import ast
import types
import sys
import converter
from tools import print_stderr
# Learner Block
with open("submission/submission.py") as f:
try:
learner_py = ast.parse(f.read())
except SyntaxError:
print_stderr(
"The notebook you provided has a syntax error that prevents it from compiling."
)
exit()
for node in learner_py.body[:]:
if not isinstance(
node, (ast.FunctionDef, ast.Import, ast.ImportFrom, ast.ClassDef)):
learner_py.body.remove(node)
learner_module = types.ModuleType("learner_mod")
learner_code = compile(learner_py, "learner_mod.py", 'exec')
sys.modules["learner_mod"] = learner_module
exec(learner_code, learner_module.__dict__)
# Solution Block
with open("solution/solution.py") as f:
solution_py = ast.parse(f.read())
for node in solution_py.body[:]: