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"""
Tools to help with tensor property propagation.
This is not intended to be imported directly; please use the exposed
functionalities in `torch.jit`.
"""
from typing import Any, List
import torch
from torch import TensorType
from torch._C import Graph
def apply_input_props_using_example(graph: Graph, example_input: List[Any]):
"""
Applies properties for each tensor in the graph inputs
using the example supplied.
"""
graph_inputs = list(graph.inputs())
if len(graph_inputs) == 0:
return
# Strip self args off for methods
in_0 = graph_inputs[0]
if isinstance(in_0.type(), torch._C.ClassType) and in_0.debugName() == "self":
graph_inputs = graph_inputs[1:]
if not len(graph_inputs) == len(example_input):
raise RuntimeError(
"Number of inputs in graph does not match number of inputs in the example")
for i, (graph_i, example_i) in enumerate(zip(graph_inputs, example_input)):
if example_i is None:
continue # Skip the type check
if isinstance(example_i, torch.Tensor) != isinstance(graph_i.type(), TensorType):
raise RuntimeError(f"Input {i} does not match type of example", graph_i, example_i)
if isinstance(example_i, torch.Tensor):
graph_i.setType(TensorType.create_from_tensor(example_i)) # type: ignore[arg-type]
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