onnx--onnx/onnx/backend/test/case/node/expand.py

# Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations

import numpy as np

import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect


class Expand(Base):
    @staticmethod
    def export_dim_changed() -> None:
        node = onnx.helper.make_node(
            "Expand",
            inputs=["data", "new_shape"],
            outputs=["expanded"],
        )
        shape = [3, 1]
        data = np.reshape(np.arange(1, np.prod(shape) + 1, dtype=np.float32), shape)
        # print(data)
        # [[1.], [2.], [3.]]
        new_shape = [2, 1, 6]
        expanded = data * np.ones(new_shape, dtype=np.float32)
        # print(expanded)
        # [[[1., 1., 1., 1., 1., 1.],
        #  [2., 2., 2., 2., 2., 2.],
        #  [3., 3., 3., 3., 3., 3.]],
        #
        # [[1., 1., 1., 1., 1., 1.],
        #  [2., 2., 2., 2., 2., 2.],
        #  [3., 3., 3., 3., 3., 3.]]]
        new_shape = np.array(new_shape, dtype=np.int64)
        expect(
            node,
            inputs=[data, new_shape],
            outputs=[expanded],
            name="test_expand_dim_changed",
        )

    @staticmethod
    def export_dim_unchanged() -> None:
        node = onnx.helper.make_node(
            "Expand",
            inputs=["data", "new_shape"],
            outputs=["expanded"],
        )
        shape = [3, 1]
        new_shape = [3, 4]
        data = np.reshape(np.arange(1, np.prod(shape) + 1, dtype=np.float32), shape)
        # print(data)
        # [[1.], [2.], [3.]]
        expanded = np.tile(data, 4)
        # print(expanded)
        # [[1., 1., 1., 1.],
        # [2., 2., 2., 2.],
        # [3., 3., 3., 3.]]
        new_shape = np.array(new_shape, dtype=np.int64)
        expect(
            node,
            inputs=[data, new_shape],
            outputs=[expanded],
            name="test_expand_dim_unchanged",
        )