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Address PR feedback: simplify comments, remove extra assertion, and improve docstrings
Co-authored-by: ProExpertProg <11367180+ProExpertProg@users.noreply.github.com>
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@ -16,8 +16,7 @@ from vllm.config import (CompilationConfig, CompilationLevel, VllmConfig,
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from vllm.envs import VLLM_USE_V1
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from vllm.envs import VLLM_USE_V1
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from vllm.forward_context import set_forward_context
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from vllm.forward_context import set_forward_context
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# Import shared test operations
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# This import automatically registers torch ops for testing (like silly.attention)
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# The standard attention operation is automatically registered when imported
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import tests.compile.test_operations
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import tests.compile.test_operations
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BATCH_SIZE = 32
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BATCH_SIZE = 32
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@ -320,9 +319,5 @@ def test_multi_graph_piecewise_compile_outputs_equal():
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):
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):
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outputs.append(run_model(vllm_config, model, inputs))
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outputs.append(run_model(vllm_config, model, inputs))
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# Generally don't expect outputs with and without inductor
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# to be bitwise equivalent
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assert torch.allclose(outputs[0], outputs[1])
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# Expect bitwise equivalence using inductor w/ and w/o cudagraph
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# Expect bitwise equivalence using inductor w/ and w/o cudagraph
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assert torch.equal(outputs[0], outputs[2])
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assert torch.equal(outputs[0], outputs[2])
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@ -15,7 +15,7 @@ from vllm.config import (CompilationConfig, CompilationLevel, CUDAGraphMode,
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from vllm.envs import VLLM_USE_V1
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from vllm.envs import VLLM_USE_V1
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from vllm.forward_context import BatchDescriptor, set_forward_context
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from vllm.forward_context import BatchDescriptor, set_forward_context
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# Import shared test operations
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# This import also automatically registers torch ops for testing (like silly.attention)
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from tests.compile.test_operations import (
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from tests.compile.test_operations import (
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get_global_counter, reset_global_counter
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get_global_counter, reset_global_counter
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)
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)
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@ -470,4 +470,4 @@ def benchmark():
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if __name__ == "__main__":
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if __name__ == "__main__":
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benchmark()
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pass
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@ -3,14 +3,7 @@
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"""
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"""
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Shared PyTorch custom operations for compilation tests.
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Shared PyTorch custom operations for compilation tests.
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This module provides a centralized place to define and register custom
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Centralizes custom operation definitions to avoid duplicate registrations.
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PyTorch operations used across multiple compilation tests. This avoids
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duplicate operation registrations that would cause RuntimeErrors when
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running tests together.
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The main "attention" operation is automatically registered when this module
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is imported. Individual test files can access the global counter functionality
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through helper functions.
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"""
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"""
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import torch
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import torch
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@ -23,7 +16,7 @@ from vllm.utils import direct_register_custom_op
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silly_lib = Library("silly", "FRAGMENT")
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silly_lib = Library("silly", "FRAGMENT")
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# Global counter that all tests can use or ignore
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# Global counter that counts the number of times attention is invoked
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_global_counter = 0
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_global_counter = 0
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