compiler_gym/envs/llvm/datasets/anghabench.py [118:132]:
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    def compile_all(self):
        n = self.size
        executor = thread_pool.get_thread_pool_executor()
        # Since the dataset is lazily compiled, simply iterating over the full
        # set of URIs will compile everything. Do this in parallel.
        futures = (
            executor.submit(self.benchmark, uri) for uri in self.benchmark_uris()
        )
        for i, future in enumerate(as_completed(futures), start=1):
            future.result()
            print(
                f"\r\033[KCompiled {i} of {n} programs ({i/n:.1%} complete)",
                flush=True,
                end="",
            )
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compiler_gym/envs/llvm/datasets/chstone.py [122:136]:
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    def compile_all(self):
        n = self.size
        executor = thread_pool.get_thread_pool_executor()
        # Since the dataset is lazily compiled, simply iterating over the full
        # set of URIs will compile everything. Do this in parallel.
        futures = (
            executor.submit(self.benchmark, uri) for uri in self.benchmark_uris()
        )
        for i, future in enumerate(as_completed(futures), start=1):
            future.result()
            print(
                f"\r\033[KCompiled {i} of {n} programs ({i/n:.1%} complete)",
                flush=True,
                end="",
            )
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