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https://github.com/luxfi/onnx-source-snapshot.git
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92 lines
2.7 KiB
Python
92 lines
2.7 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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class Unsqueeze(Base):
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@staticmethod
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def export_unsqueeze_one_axis() -> None:
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x = np.random.randn(3, 4, 5).astype(np.float32)
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for i in range(x.ndim):
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axes = np.array([i]).astype(np.int64)
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node = onnx.helper.make_node(
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"Unsqueeze",
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inputs=["x", "axes"],
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outputs=["y"],
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)
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y = np.expand_dims(x, axis=i)
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expect(
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node,
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inputs=[x, axes],
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outputs=[y],
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name="test_unsqueeze_axis_" + str(i),
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)
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@staticmethod
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def export_unsqueeze_two_axes() -> None:
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x = np.random.randn(3, 4, 5).astype(np.float32)
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axes = np.array([1, 4]).astype(np.int64)
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node = onnx.helper.make_node(
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"Unsqueeze",
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inputs=["x", "axes"],
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outputs=["y"],
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)
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y = np.expand_dims(x, axis=1)
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y = np.expand_dims(y, axis=4)
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expect(node, inputs=[x, axes], outputs=[y], name="test_unsqueeze_two_axes")
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@staticmethod
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def export_unsqueeze_three_axes() -> None:
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x = np.random.randn(3, 4, 5).astype(np.float32)
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axes = np.array([2, 4, 5]).astype(np.int64)
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node = onnx.helper.make_node(
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"Unsqueeze",
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inputs=["x", "axes"],
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outputs=["y"],
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)
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y = np.expand_dims(x, axis=2)
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y = np.expand_dims(y, axis=4)
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y = np.expand_dims(y, axis=5)
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expect(node, inputs=[x, axes], outputs=[y], name="test_unsqueeze_three_axes")
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@staticmethod
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def export_unsqueeze_unsorted_axes() -> None:
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x = np.random.randn(3, 4, 5).astype(np.float32)
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axes = np.array([5, 4, 2]).astype(np.int64)
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node = onnx.helper.make_node(
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"Unsqueeze",
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inputs=["x", "axes"],
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outputs=["y"],
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)
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y = np.expand_dims(x, axis=2)
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y = np.expand_dims(y, axis=4)
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y = np.expand_dims(y, axis=5)
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expect(node, inputs=[x, axes], outputs=[y], name="test_unsqueeze_unsorted_axes")
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@staticmethod
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def export_unsqueeze_negative_axes() -> None:
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node = onnx.helper.make_node(
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"Unsqueeze",
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inputs=["x", "axes"],
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outputs=["y"],
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)
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x = np.random.randn(1, 3, 1, 5).astype(np.float32)
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axes = np.array([-2]).astype(np.int64)
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y = np.expand_dims(x, axis=-2)
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expect(node, inputs=[x, axes], outputs=[y], name="test_unsqueeze_negative_axes")
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