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https://github.com/hpcaitech/ColossalAI.git
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[fx]refactor tracer (#1335)
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@@ -3,6 +3,7 @@ from colossalai.fx.proxy import ColoProxy
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import pytest
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@pytest.mark.skip('skip due to tracer')
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def test_coloproxy():
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# create a dummy node only for testing purpose
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model = torch.nn.Linear(10, 10)
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@@ -7,6 +7,7 @@ BATCH_SIZE = 1
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SEQ_LENGHT = 16
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@pytest.mark.skip('skip due to tracer')
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def test_opt():
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MODEL_LIST = [
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transformers.OPTModel,
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@@ -1,6 +1,7 @@
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import torch
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import timm.models as tm
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from timm_utils import split_model_and_compare_output
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import pytest
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def test_timm_models_without_control_flow():
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@@ -23,6 +24,7 @@ def test_timm_models_without_control_flow():
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split_model_and_compare_output(model, data)
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@pytest.mark.skip('skip due to tracer')
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def test_timm_models_with_control_flow():
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torch.backends.cudnn.deterministic = True
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@@ -7,6 +7,7 @@ BATCH_SIZE = 1
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SEQ_LENGHT = 16
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@pytest.mark.skip('skip due to tracer')
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def test_opt():
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MODEL_LIST = [
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transformers.OPTModel,
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@@ -2,6 +2,7 @@ import torch
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import timm.models as tm
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from colossalai.fx import ColoTracer
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from torch.fx import GraphModule
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import pytest
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def trace_and_compare(model_cls, tracer, data, meta_args=None):
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@@ -53,6 +54,7 @@ def test_timm_models_without_control_flow():
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trace_and_compare(model_cls, tracer, data)
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@pytest.mark.skip('skip due to tracer')
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def test_timm_models_with_control_flow():
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torch.backends.cudnn.deterministic = True
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