Fix torch bfloat import version (#9089)
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@ -19,7 +19,7 @@ from torch.optim import LBFGS, Optimizer
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import pytorch_lightning as pl
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from pytorch_lightning.plugins.precision.mixed import MixedPrecisionPlugin
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from pytorch_lightning.utilities import _NATIVE_AMP_AVAILABLE, _TORCH_GREATER_EQUAL_1_10, AMPType
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from pytorch_lightning.utilities import _NATIVE_AMP_AVAILABLE, _TORCH_BFLOAT_AVAILABLE, AMPType
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from pytorch_lightning.utilities.exceptions import MisconfigurationException
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@ -46,7 +46,7 @@ class NativeMixedPrecisionPlugin(MixedPrecisionPlugin):
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def _select_precision_dtype(self, precision: Union[int, str] = 16) -> torch.dtype:
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if precision == "bf16":
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if not _TORCH_GREATER_EQUAL_1_10:
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if not _TORCH_BFLOAT_AVAILABLE:
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raise MisconfigurationException(
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"To use bfloat16 with native amp you must install torch greater or equal to 1.10."
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)
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@ -44,6 +44,7 @@ from pytorch_lightning.utilities.imports import ( # noqa: F401
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_OMEGACONF_AVAILABLE,
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_POPTORCH_AVAILABLE,
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_RICH_AVAILABLE,
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_TORCH_BFLOAT_AVAILABLE,
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_TORCH_GREATER_EQUAL_1_7,
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_TORCH_GREATER_EQUAL_1_8,
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_TORCH_GREATER_EQUAL_1_9,
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@ -87,8 +87,13 @@ _NATIVE_AMP_AVAILABLE = _module_available("torch.cuda.amp") and hasattr(torch.cu
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_OMEGACONF_AVAILABLE = _module_available("omegaconf")
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_POPTORCH_AVAILABLE = _module_available("poptorch")
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_RICH_AVAILABLE = _module_available("rich")
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_TORCH_BFLOAT_AVAILABLE = _compare_version(
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"torch", operator.ge, "1.10.0.dev20210820"
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) # todo: swap to 1.10.0 once released
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_TORCH_QUANTIZE_AVAILABLE = bool([eg for eg in torch.backends.quantized.supported_engines if eg != "none"])
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_TORCH_SHARDED_TENSOR_AVAILABLE = _compare_version("torch", operator.ge, "1.10.0.dev20210809")
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_TORCH_SHARDED_TENSOR_AVAILABLE = _compare_version(
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"torch", operator.ge, "1.10.0.dev20210809"
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) # todo: swap to 1.10.0 once released
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_TORCHTEXT_AVAILABLE = _module_available("torchtext")
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_TORCHVISION_AVAILABLE = _module_available("torchvision")
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_TORCHMETRICS_LOWER_THAN_0_3 = _compare_version("torchmetrics", operator.lt, "0.3.0")
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@ -22,7 +22,7 @@ from torch.utils.data import DataLoader
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import tests.helpers.utils as tutils
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from pytorch_lightning import Trainer
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from pytorch_lightning.plugins.environments import SLURMEnvironment
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from pytorch_lightning.utilities import _TORCH_GREATER_EQUAL_1_10
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from pytorch_lightning.utilities import _TORCH_BFLOAT_AVAILABLE
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from pytorch_lightning.utilities.exceptions import MisconfigurationException
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from tests.helpers import BoringModel, RandomDataset
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from tests.helpers.runif import RunIf
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@ -71,7 +71,7 @@ class AMPTestModel(BoringModel):
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16,
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pytest.param(
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"bf16",
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marks=pytest.mark.skipif(not _TORCH_GREATER_EQUAL_1_10, reason="torch.bfloat16 not available"),
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marks=pytest.mark.skipif(not _TORCH_BFLOAT_AVAILABLE, reason="torch.bfloat16 not available"),
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),
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],
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)
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