Shortcuts

Source code for torch.onnx

# mypy: allow-untyped-defs
from torch import _C
from torch._C import _onnx as _C_onnx
from torch._C._onnx import (
    _CAFFE2_ATEN_FALLBACK,
    OperatorExportTypes,
    TensorProtoDataType,
    TrainingMode,
)

from . import (  # usort:skip. Keep the order instead of sorting lexicographically
    _deprecation,
    errors,
    symbolic_caffe2,
    symbolic_helper,
    symbolic_opset7,
    symbolic_opset8,
    symbolic_opset9,
    symbolic_opset10,
    symbolic_opset11,
    symbolic_opset12,
    symbolic_opset13,
    symbolic_opset14,
    symbolic_opset15,
    symbolic_opset16,
    symbolic_opset17,
    symbolic_opset18,
    symbolic_opset19,
    symbolic_opset20,
    utils,
)

# TODO(After 1.13 release): Remove the deprecated SymbolicContext
from ._exporter_states import ExportTypes, SymbolicContext
from ._type_utils import JitScalarType
from .errors import CheckerError  # Backwards compatibility
from .utils import (
    _optimize_graph,
    _run_symbolic_function,
    _run_symbolic_method,
    export,
    export_to_pretty_string,
    is_in_onnx_export,
    register_custom_op_symbolic,
    select_model_mode_for_export,
    unregister_custom_op_symbolic,
)

from ._internal.exporter import (  # usort:skip. needs to be last to avoid circular import
    DiagnosticOptions,
    ExportOptions,
    ONNXProgram,
    ONNXProgramSerializer,
    ONNXRuntimeOptions,
    InvalidExportOptionsError,
    OnnxExporterError,
    OnnxRegistry,
    dynamo_export,
    enable_fake_mode,
)

from ._internal.onnxruntime import (
    is_onnxrt_backend_supported,
    OrtBackend as _OrtBackend,
    OrtBackendOptions as _OrtBackendOptions,
    OrtExecutionProvider as _OrtExecutionProvider,
)

__all__ = [
    # Modules
    "symbolic_helper",
    "utils",
    "errors",
    # All opsets
    "symbolic_caffe2",
    "symbolic_opset7",
    "symbolic_opset8",
    "symbolic_opset9",
    "symbolic_opset10",
    "symbolic_opset11",
    "symbolic_opset12",
    "symbolic_opset13",
    "symbolic_opset14",
    "symbolic_opset15",
    "symbolic_opset16",
    "symbolic_opset17",
    "symbolic_opset18",
    "symbolic_opset19",
    "symbolic_opset20",
    # Enums
    "ExportTypes",
    "OperatorExportTypes",
    "TrainingMode",
    "TensorProtoDataType",
    "JitScalarType",
    # Public functions
    "export",
    "export_to_pretty_string",
    "is_in_onnx_export",
    "select_model_mode_for_export",
    "register_custom_op_symbolic",
    "unregister_custom_op_symbolic",
    "disable_log",
    "enable_log",
    # Errors
    "CheckerError",  # Backwards compatibility
    # Dynamo Exporter
    "DiagnosticOptions",
    "ExportOptions",
    "ONNXProgram",
    "ONNXProgramSerializer",
    "ONNXRuntimeOptions",
    "InvalidExportOptionsError",
    "OnnxExporterError",
    "OnnxRegistry",
    "dynamo_export",
    "enable_fake_mode",
    # DORT / torch.compile
    "is_onnxrt_backend_supported",
]

# Set namespace for exposed private names
ExportTypes.__module__ = "torch.onnx"
JitScalarType.__module__ = "torch.onnx"
ExportOptions.__module__ = "torch.onnx"
ONNXProgram.__module__ = "torch.onnx"
ONNXProgramSerializer.__module__ = "torch.onnx"
ONNXRuntimeOptions.__module__ = "torch.onnx"
dynamo_export.__module__ = "torch.onnx"
InvalidExportOptionsError.__module__ = "torch.onnx"
OnnxExporterError.__module__ = "torch.onnx"
enable_fake_mode.__module__ = "torch.onnx"
OnnxRegistry.__module__ = "torch.onnx"
DiagnosticOptions.__module__ = "torch.onnx"
is_onnxrt_backend_supported.__module__ = "torch.onnx"
_OrtExecutionProvider.__module__ = "torch.onnx"
_OrtBackendOptions.__module__ = "torch.onnx"
_OrtBackend.__module__ = "torch.onnx"

producer_name = "pytorch"
producer_version = _C_onnx.PRODUCER_VERSION


@_deprecation.deprecated(
    since="1.12.0", removed_in="2.0", instructions="use `torch.onnx.export` instead"
)
def _export(*args, **kwargs):
    return utils._export(*args, **kwargs)


# TODO(justinchuby): Deprecate these logging functions in favor of the new diagnostic module.

# Returns True iff ONNX logging is turned on.
is_onnx_log_enabled = _C._jit_is_onnx_log_enabled


[docs]def enable_log() -> None: r"""Enables ONNX logging.""" _C._jit_set_onnx_log_enabled(True)
[docs]def disable_log() -> None: r"""Disables ONNX logging.""" _C._jit_set_onnx_log_enabled(False)
"""Sets output stream for ONNX logging. Args: stream_name (str, default "stdout"): Only 'stdout' and 'stderr' are supported as ``stream_name``. """ set_log_stream = _C._jit_set_onnx_log_output_stream """A simple logging facility for ONNX exporter. Args: args: Arguments are converted to string, concatenated together with a newline character appended to the end, and flushed to output stream. """ log = _C._jit_onnx_log

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources