wehub-resource-sync
74 lines
3.1 KiB
ReStructuredText
74 lines
3.1 KiB
ReStructuredText
.. Licensed to the Apache Software Foundation (ASF) under one
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or more contributor license agreements. See the NOTICE file
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distributed with this work for additional information
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regarding copyright ownership. The ASF licenses this file
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to you under the Apache License, Version 2.0 (the
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"License"); you may not use this file except in compliance
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with the License. You may obtain a copy of the License at
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.. http://www.apache.org/licenses/LICENSE-2.0
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.. Unless required by applicable law or agreed to in writing,
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software distributed under the License is distributed on an
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"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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KIND, either express or implied. See the License for the
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specific language governing permissions and limitations
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under the License.
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TVM Errors
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==========
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TVM may raise errors from Python code, from C++ code reached through the
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FFI, or from generated runtime modules. Error messages usually include
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a Python stack trace, and may also include a C++ stack trace when the
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error crosses the TVM FFI boundary.
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Some errors report invalid user input, unsupported operators, missing
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runtime features, or unavailable hardware. Others report a failed
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internal check, usually raised by ``TVM_FFI_ICHECK`` or
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``TVM_FFI_THROW`` in C++ code. Internal check failures often indicate
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that TVM reached a state that the implementation did not expect.
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What to Check First
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-------------------
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- Make sure the TVM Python package and native libraries come from the
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same build. A common symptom of a mismatched environment is importing
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Python files from one checkout while loading ``libtvm`` from another.
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- Check that the required runtime is enabled in ``config.cmake``. For
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example, CUDA tests and CUDA compilation require a TVM build with
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CUDA support enabled.
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- Check that the target hardware is available to the process. GPU
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tests may be skipped or fail if the device is not visible inside the
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current container or environment.
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- If the error occurs while importing or converting a model, reduce the
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input to the smallest model, operator, or shape that reproduces the
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issue.
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Reporting an Issue
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------------------
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Search the `Apache TVM Discuss Forum <https://discuss.tvm.apache.org/>`_
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and the `TVM issue tracker <https://github.com/apache/tvm/issues>`_
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for the exact error message first. If you do not find an existing
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report, include the following details when starting a new discussion or
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filing an issue:
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- The TVM version or git commit hash.
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- The Python version, operating system, and hardware.
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- The target and runtime being used, such as LLVM, CUDA, Vulkan, or RPC.
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- The relevant build configuration from ``config.cmake``.
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- A minimal script, model, input shape, or IR module that reproduces the
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failure.
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- The full error message, including both Python and C++ stack traces
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when present.
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Developer Notes
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---------------
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For guidance on raising typed errors from TVM code, see
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:ref:`error-handling-guide`. That guide covers when to use specific
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error types, how C++ error prefixes map to Python exceptions, and how
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``TVM_FFI_ICHECK`` interacts with TVM's error handling.
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