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Ray version upgrade #4302

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Merged
merged 3 commits into from
Jul 12, 2024
Merged

Ray version upgrade #4302

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2a2edc1
upgrade ray
suzhoum Jun 27, 2024
68ee339
tighten upperbound
suzhoum Jul 9, 2024
1ad9ccc
try fixing intermittant dataloader issue
suzhoum Jul 10, 2024
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2 changes: 1 addition & 1 deletion common/src/autogluon/common/utils/try_import.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@ def try_import_mxboard():


def try_import_ray() -> ModuleType:
RAY_MAX_VERSION = "2.11.0" # sync with core/setup.py
RAY_MAX_VERSION = "2.32.0" # sync with core/setup.py
ray_max_version_os_map = dict(
Darwin=RAY_MAX_VERSION,
Windows=RAY_MAX_VERSION,
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4 changes: 2 additions & 2 deletions core/setup.py
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Expand Up @@ -48,10 +48,10 @@

extras_require = {
"ray": [
"ray[default]>=2.10.0,<2.11", # sync with common/src/autogluon/common/utils/try_import.py
"ray[default]>=2.10.0,<2.32", # sync with common/src/autogluon/common/utils/try_import.py
],
"raytune": [
"ray[default,tune]>=2.10.0,<2.11", # sync with common/src/autogluon/common/utils/try_import.py
"ray[default,tune]>=2.10.0,<2.32", # sync with common/src/autogluon/common/utils/try_import.py
# TODO: consider alternatives as hyperopt is not actively maintained.
"hyperopt>=0.2.7,<0.2.8", # This is needed for the bayes search to work.
# 'GPy>=1.10.0,<1.11.0' # TODO: Enable this once PBT/PB2 are supported by ray lightning
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12 changes: 10 additions & 2 deletions multimodal/tests/unittests/others/test_dump_model.py
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Expand Up @@ -45,7 +45,11 @@ def test_dump_hf_text():
predictor_1 = MultiModalPredictor(
label=dataset.label_columns[0], problem_type=dataset.problem_type, eval_metric=dataset.metric
)
hyperparameters = {"optimization.max_epochs": 1, "model.hf_text.checkpoint_name": base_model_name}
hyperparameters = {
"optimization.max_epochs": 1,
"model.hf_text.checkpoint_name": base_model_name,
"env.num_workers": 0, # https://github.com/pytorch/pytorch/issues/33296
}
predictor_1.fit(train_data=dataset.train_df, hyperparameters=hyperparameters, time_limit=5, seed=42)
predictor_1.dump_model(save_path=model_dump_path)

Expand All @@ -54,7 +58,11 @@ def test_dump_hf_text():
predictor_2 = MultiModalPredictor(
label=dataset.label_columns[0], problem_type=dataset.problem_type, eval_metric=dataset.metric
)
hyperparameters = {"optimization.max_epochs": 1, "model.hf_text.checkpoint_name": f"{model_dump_path}/hf_text"}
hyperparameters = {
"optimization.max_epochs": 1,
"model.hf_text.checkpoint_name": f"{model_dump_path}/hf_text",
"env.num_workers": 0, # https://github.com/pytorch/pytorch/issues/33296
}
predictor_2.fit(train_data=dataset.train_df, hyperparameters=hyperparameters, time_limit=5, seed=42)


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