Source code for polygraphy.backend.pluginref.runner

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# SPDX-License-Identifier: Apache-2.0
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import copy
import time
from collections import OrderedDict

from polygraphy import mod, util
from polygraphy.backend.base import BaseRunner
from polygraphy.backend.pluginref.references import OP_REGISTRY
from polygraphy.logger import G_LOGGER

np = mod.lazy_import("numpy")
onnx_util = mod.lazy_import("polygraphy.backend.onnx.util")

[docs] @mod.export() class PluginRefRunner(BaseRunner): """ Runs inference using custom CPU reference implementations """ def __init__(self, graph, name=None): """ Args: graph (Union[onnx_graphsurgeon.Graph, Callable() -> onnx_graphsurgeon.Graph]): An ONNX-GraphSurgeon graph or a callable that returns one. name (str): The human-readable name prefix to use for this runner. A runner count and timestamp will be appended to this prefix. """ super().__init__(name=name, prefix="pluginref-runner") self._graph = graph @util.check_called_by("activate") def activate_impl(self): self.graph, _ = util.invoke_if_callable(self._graph) @util.check_called_by("get_input_metadata") def get_input_metadata_impl(self): return onnx_util.meta_from_gs_tensors(self.graph.inputs) @util.check_called_by("infer") def infer_impl(self, feed_dict): start = time.time() intermediate_tensors = copy.copy(feed_dict) for node in self.graph.nodes: if node.op not in OP_REGISTRY: G_LOGGER.critical( f"Op: {node.op} does not have a reference implementation registered!" ) intermediate_tensors.update( OP_REGISTRY[node.op](node, intermediate_tensors) ) outputs = OrderedDict() for out in self.graph.outputs: outputs[] = intermediate_tensors[] end = time.time() self.inference_time = end - start return outputs @util.check_called_by("deactivate") def deactivate_impl(self): del self.graph