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from ._TRTInterpreter import * # noqa: F403 | ||
from .aten_ops_converters import * # noqa: F403 | ||
from .conversion import * # noqa: F403 | ||
from .op_evaluators import * # noqa: F403 | ||
from .truncate_long_and_double import repair_long_or_double_inputs |
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condition, | ||
elementwise, | ||
embedding, | ||
evaluators, | ||
matmul, | ||
normalization, | ||
permutation, | ||
|
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import logging | ||
import operator | ||
from typing import Dict, Sequence, Tuple, Union | ||
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from torch.fx.node import Argument, Node, Target | ||
from torch_tensorrt.fx.types import TRTNetwork, TRTTensor | ||
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from .converter_registry import ConverterRegistry, dynamo_tensorrt_converter | ||
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_LOGGER: logging.Logger = logging.getLogger(__name__) | ||
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def getitem_validator(getitem_node: Node) -> bool: | ||
from torch_tensorrt.dynamo.conversion.converter_registry import DYNAMO_CONVERTERS | ||
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# Getitem nodes can only be converted if their parent node also can | ||
return getitem_node.args[0] in DYNAMO_CONVERTERS | ||
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# TODO: Subsequent evaluators should be registered here with their own validators | ||
@dynamo_tensorrt_converter(operator.getitem, capability_validator=getitem_validator) | ||
def generic_evaluator( | ||
network: TRTNetwork, | ||
target: Target, | ||
args: Tuple[Argument, ...], | ||
kwargs: Dict[str, Argument], | ||
name: str, | ||
) -> Union[TRTTensor, Sequence[TRTTensor]]: | ||
_LOGGER.debug( | ||
f"Evaluating {ConverterRegistry.qualified_name_or_str(target)} on object with name: {name}" | ||
) | ||
return target(*args) |
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