wehub-resource-sync
118 lines
5.2 KiB
Python
118 lines
5.2 KiB
Python
#
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# SPDX-FileCopyrightText: Copyright (c) 1993-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from polygraphy import config as polygraphy_config, mod, util
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from polygraphy.backend.trt.config import _CreateConfigCommon
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from polygraphy.backend.trt.util import inherit_and_extend_docstring
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from polygraphy.logger import G_LOGGER
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from polygraphy.mod.trt_importer import lazy_import_trt
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trt = lazy_import_trt()
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@mod.export(funcify=True, func_name="create_config_rtx")
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class CreateConfigRTX(_CreateConfigCommon):
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"""
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Functor that creates an IBuilderConfig with TensorRT-RTX specific features.
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"""
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@inherit_and_extend_docstring(_CreateConfigCommon.__init__)
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def __init__(
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self,
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use_gpu=None,
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compute_capabilities=None,
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**kwargs
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):
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"""
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Creates an IBuilderConfig with TensorRT-RTX specific features.
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Args:
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use_gpu (bool):
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Whether to use the current GPU device as target for engine compilation.
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Equivalent to setting ComputeCapability.CURRENT. This is mutually exclusive with compute_capabilities.
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Defaults to False.
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compute_capabilities (List[Tuple[int, int]]):
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List of (major, minor) compute capability tuples to target for engine compilation.
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This is mutually exclusive with use_gpu. When specified, the engine can only run on devices
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with the specified compute capabilities.
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Defaults to None.
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"""
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super().__init__(**kwargs)
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self.use_gpu = util.default(use_gpu, False)
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self.compute_capabilities = compute_capabilities
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if self.use_gpu and self.compute_capabilities:
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G_LOGGER.critical("use_gpu and compute_capabilities are mutually exclusive.")
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self._validator()
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def _validator(self):
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"""
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Validates initialization parameters for TensorRT-RTX specific features.
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"""
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if self.use_gpu or self.compute_capabilities is not None:
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if not polygraphy_config.USE_TENSORRT_RTX:
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G_LOGGER.critical("--compute-capabilities and --use-gpu settings are only supported with USE_TENSORRT_RTX=1.")
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# Validate compute capabilities format and availability
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if self.compute_capabilities:
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for major, minor in self.compute_capabilities:
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cap_name = f"SM{major}{minor}"
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if not hasattr(trt.ComputeCapability, cap_name):
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G_LOGGER.critical(f"Compute capability {major}.{minor} ({cap_name})"
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" not supported by this TensorRT-RTX version.")
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def _configure_flags(self, builder, network, config):
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"""
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Validates and configures TensorRT-RTX-specific features.
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Args:
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builder (trt.Builder): The TensorRT builder
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network (trt.INetworkDefinition): The TensorRT network
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config (trt.IBuilderConfig): The TensorRT builder config to modify
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"""
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# Set compute capabilities if specified
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if self.use_gpu or self.compute_capabilities is not None:
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try:
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if self.use_gpu:
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# Use current GPU device
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config.num_compute_capabilities = 1
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config.set_compute_capability(trt.ComputeCapability.CURRENT, 0)
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G_LOGGER.info("Using current GPU device for engine compilation (ComputeCapability.CURRENT)")
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elif self.compute_capabilities:
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# Set specific compute capabilities
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config.num_compute_capabilities = len(self.compute_capabilities)
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G_LOGGER.info(f"Setting {len(self.compute_capabilities)} target compute capabilities: {self.compute_capabilities}")
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for i, (major, minor) in enumerate(self.compute_capabilities):
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cap_name = f"SM{major}{minor}"
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compute_cap = getattr(trt.ComputeCapability, cap_name)
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config.set_compute_capability(compute_cap, i)
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except Exception as e:
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G_LOGGER.critical(f"Failed to set compute capabilities: {e}. You are likely not using a TensorRT-RTX build.")
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@util.check_called_by("__call__")
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def call_impl(self, builder, network):
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"""
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Callable implementation that creates and configures the IBuilderConfig with TensorRT-RTX features.
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"""
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# Enable all common config options
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config = super().call_impl(builder, network)
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self._configure_flags(builder, network, config)
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return config
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