# 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 ConstantOfShape(Base):
    @staticmethod
    def export_float_ones() -> None:
        x = np.array([4, 3, 2]).astype(np.int64)
        tensor_value = onnx.helper.make_tensor(
            "value", onnx.TensorProto.FLOAT, [1], [1]
        )
        node = onnx.helper.make_node(
            "ConstantOfShape",
            inputs=["x"],
            outputs=["y"],
            value=tensor_value,
        )

        y = np.ones(x, dtype=np.float32)
        expect(node, inputs=[x], outputs=[y], name="test_constantofshape_float_ones")

    @staticmethod
    def export_int32_zeros() -> None:
        x = np.array([10, 6]).astype(np.int64)
        tensor_value = onnx.helper.make_tensor(
            "value", onnx.TensorProto.INT32, [1], [0]
        )
        node = onnx.helper.make_node(
            "ConstantOfShape",
            inputs=["x"],
            outputs=["y"],
            value=tensor_value,
        )
        y = np.zeros(x, dtype=np.int32)
        expect(node, inputs=[x], outputs=[y], name="test_constantofshape_int_zeros")

    @staticmethod
    def export_int32_shape_zero() -> None:
        x = np.array(
            [
                0,
            ]
        ).astype(np.int64)
        tensor_value = onnx.helper.make_tensor(
            "value", onnx.TensorProto.INT32, [1], [0]
        )
        node = onnx.helper.make_node(
            "ConstantOfShape",
            inputs=["x"],
            outputs=["y"],
            value=tensor_value,
        )
        y = np.zeros(x, dtype=np.int32)
        expect(
            node, inputs=[x], outputs=[y], name="test_constantofshape_int_shape_zero"
        )