mirror of https://github.com/llvm/torch-mlir
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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# See https://llvm.org/LICENSE.txt for license information.
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# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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"""Value coders for Numpy types."""
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import numpy as np
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from typing import Union
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from _npcomp.mlir import ir
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from ... import logging
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from ...interfaces import *
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__all__ = [
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"CreateNumpyValueCoder",
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]
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_NotImplementedType = type(NotImplemented)
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class NdArrayValueCoder(ValueCoder):
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"""Value coder for numpy types."""
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__slots__ = []
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def code_py_value_as_const(self, env: Environment,
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py_value) -> Union[_NotImplementedType, ir.Value]:
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# TODO: Query for ndarray compat (for duck typed and such)
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# TODO: Have a higher level name resolution signal which indicates const
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ir_h = env.ir_h
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if isinstance(py_value, np.ndarray):
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dense_attr = ir_h.context.dense_elements_attr(py_value)
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tensor_type = dense_attr.type
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tensor_value = ir_h.constant_op(tensor_type, dense_attr).result
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return ir_h.numpy_create_array_from_tensor_op(tensor_value).result
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return NotImplemented
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def CreateNumpyValueCoder() -> ValueCoder:
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return ValueCoderChain((NdArrayValueCoder(),))
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