mirror of
https://github.com/luxfi/onnx-source-snapshot.git
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93 lines
3.2 KiB
Python
93 lines
3.2 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 Equal(Base):
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@staticmethod
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def export() -> None:
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node = onnx.helper.make_node(
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"Equal",
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inputs=["x", "y"],
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outputs=["z"],
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)
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x = (np.random.randn(3, 4, 5) * 10).astype(np.int32)
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y = (np.random.randn(3, 4, 5) * 10).astype(np.int32)
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal")
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x = (np.random.randn(3, 4, 5) * 10).astype(np.int8)
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y = (np.random.randn(3, 4, 5) * 10).astype(np.int8)
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_int8")
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x = (np.random.randn(3, 4, 5) * 10).astype(np.int16)
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y = (np.random.randn(3, 4, 5) * 10).astype(np.int16)
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_int16")
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x = np.random.randint(24, size=(3, 4, 5), dtype=np.uint8)
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y = np.random.randint(24, size=(3, 4, 5), dtype=np.uint8)
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_uint8")
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x = np.random.randint(24, size=(3, 4, 5), dtype=np.uint16)
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y = np.random.randint(24, size=(3, 4, 5), dtype=np.uint16)
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_uint16")
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x = np.random.randint(24, size=(3, 4, 5), dtype=np.uint32)
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y = np.random.randint(24, size=(3, 4, 5), dtype=np.uint32)
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_uint32")
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x = np.random.randint(24, size=(3, 4, 5), dtype=np.uint64)
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y = np.random.randint(24, size=(3, 4, 5), dtype=np.uint64)
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_uint64")
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@staticmethod
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def export_equal_broadcast() -> None:
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node = onnx.helper.make_node(
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"Equal",
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inputs=["x", "y"],
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outputs=["z"],
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)
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x = (np.random.randn(3, 4, 5) * 10).astype(np.int32)
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y = (np.random.randn(5) * 10).astype(np.int32)
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_bcast")
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@staticmethod
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def export_equal_string() -> None:
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node = onnx.helper.make_node(
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"Equal",
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inputs=["x", "y"],
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outputs=["z"],
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)
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x = np.array(["string1", "string2"], dtype=np.dtype(object))
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y = np.array(["string1", "string3"], dtype=np.dtype(object))
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_string")
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@staticmethod
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def export_equal_string_broadcast() -> None:
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node = onnx.helper.make_node(
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"Equal",
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inputs=["x", "y"],
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outputs=["z"],
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)
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x = np.array(["string1", "string2"], dtype=np.dtype(object))
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y = np.array(["string1"], dtype=np.dtype(object))
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z = np.equal(x, y)
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expect(node, inputs=[x, y], outputs=[z], name="test_equal_string_broadcast")
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