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Replace device check of TORCH_INTERNAL_ASSERT with TORCH_CHECK (#155318)
Fixes #136849 ## Test Result ```python >>> import torch >>> device = torch.cuda.device_count() + 1 >>> torch.cuda.current_stream(device) # INTERNAL ASSERT FAILED Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/zong/code/pytorch/torch/cuda/__init__.py", line 1083, in current_stream streamdata = torch._C._cuda_getCurrentStream( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ RuntimeError: Device index value 3 is out of index range [0, 2) >>> torch.cuda.default_stream(device) # INTERNAL ASSERT FAILED Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/zong/code/pytorch/torch/cuda/__init__.py", line 1101, in default_stream streamdata = torch._C._cuda_getDefaultStream( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ RuntimeError: Device index value 3 is out of index range [0, 2) >>> torch.cuda.set_per_process_memory_fraction(0.5, device) # INTERNAL ASSERT FAILED Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/zong/code/pytorch/torch/cuda/memory.py", line 193, in set_per_process_memory_fraction torch._C._cuda_setMemoryFraction(fraction, device) RuntimeError: Allocator not initialized for device : did you call init? ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/155318 Approved by: https://github.com/albanD
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@ -1061,7 +1061,7 @@ print(t.is_pinned())
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torch.accelerator.set_stream(s2)
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self.assertEqual(torch.accelerator.current_stream().stream_id, s2.stream_id)
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with self.assertRaisesRegex(
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RuntimeError, "device_index >= 0 && device_index < num_gpus"
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RuntimeError, "Device index value .* is out of index range"
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):
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torch.accelerator.current_stream(torch.accelerator.device_count())
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