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JitScalarType
class torch.onnx.JitScalarType(value)
-
Scalar types defined in torch.
Use
JitScalarType
to convert from torch and JIT scalar types to ONNX scalar types.Examples
>>> JitScalarType.from_value(torch.ones(1, 2)).onnx_type() TensorProtoDataType.FLOAT
>>> JitScalarType.from_value(torch_c_value_with_type_float).onnx_type() TensorProtoDataType.FLOAT
>>> JitScalarType.from_dtype(torch.get_default_dtype).onnx_type() TensorProtoDataType.FLOAT
classmethod from_dtype(dtype)
[source]-
Convert a torch dtype to JitScalarType.
Note: DO NOT USE this API when dtype comes from a torch._C.Value.type() calls.
-
A “RuntimeError: INTERNAL ASSERT FAILED at “../aten/src/ATen/core/jit_type_base.h” can be raised in several scenarios where shape info is not present. Instead use
from_value
API which is safer.
- Parameters
-
dtype (Optional[dtype]) – A torch.dtype to create a JitScalarType from
- Returns
-
JitScalarType
- Raises
-
OnnxExporterError – if dtype is not a valid torch.dtype or if it is None.
- Return type
classmethod from_value(value, default=None)
[source]-
Create a JitScalarType from an value’s scalar type.
- Parameters
- Returns
-
JitScalarType.
- Raises
-
- OnnxExporterError – if value does not have a valid scalar type and default is None.
- SymbolicValueError – when value.type()’s info are empty and default is None
- Return type
onnx_compatible()
[source]-
Return whether this JitScalarType is compatible with ONNX.
- Return type
onnx_type()
[source]-
Convert a JitScalarType to an ONNX data type.
- Return type
-
TensorProtoDataType
scalar_name()
[source]-
Convert a JitScalarType to a JIT scalar type name.
- Return type
-
Literal[‘Byte’, ‘Char’, ‘Double’, ‘Float’, ‘Half’, ‘Int’, ‘Long’, ‘Short’, ‘Bool’, ‘ComplexHalf’, ‘ComplexFloat’, ‘ComplexDouble’, ‘QInt8’, ‘QUInt8’, ‘QInt32’, ‘BFloat16’, ‘Float8E5M2’, ‘Float8E4M3FN’, ‘Undefined’]
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PyTorch has a BSD-style license, as found in the LICENSE file.
https://pytorch.org/docs/2.1/generated/torch.onnx.JitScalarType.html