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https://github.com/luxfi/onnx-source-snapshot.git
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61 lines
1.6 KiB
Python
61 lines
1.6 KiB
Python
# Copyright (c) ONNX Project Contributors
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#
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# SPDX-License-Identifier: Apache-2.0
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from __future__ import annotations
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import numpy as np
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import onnx
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from onnx.backend.test.case.base import Base
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from onnx.backend.test.case.node import expect
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# Reference implementation of shape op
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def shape_reference_impl(x, start=None, end=None): # type: ignore
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dims = x.shape[start:end]
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return np.array(dims).astype(np.int64)
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def test_shape(testname, xval, start=None, end=None): # type: ignore
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node = onnx.helper.make_node(
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"Shape", inputs=["x"], outputs=["y"], start=start, end=end
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)
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yval = shape_reference_impl(xval, start, end)
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expect(node, inputs=[xval], outputs=[yval], name="test_shape" + testname)
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class Shape(Base):
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@staticmethod
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def export() -> None:
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x = np.array(
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[
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[1, 2, 3],
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[4, 5, 6],
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]
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).astype(np.float32)
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test_shape("_example", x) # preserve names of original test cases
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x = np.random.randn(3, 4, 5).astype(np.float32)
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test_shape("", x) # preserve names of original test cases
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test_shape("_start_1", x, start=1)
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test_shape("_end_1", x, end=1)
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test_shape("_start_negative_1", x, start=-1)
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test_shape("_end_negative_1", x, end=-1)
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test_shape("_start_1_end_negative_1", x, start=1, end=-1)
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test_shape("_start_1_end_2", x, start=1, end=2)
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test_shape("_clip_start", x, start=-10)
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test_shape("_clip_end", x, end=10)
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test_shape("_start_greater_than_end", x, start=2, end=1)
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