# Copyright 2025 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Generate data for test."""
import numpy as np

def get_init_params(input_size, output_size):
    # Generate initialization parameters
    np.random.seed(42)
    weight_shape = (input_size, output_size)
    return {
        "inputs": 0.01 * np.random.randn(2, 2, input_size),
        "weight_tensor_input": 0.01 * np.random.randn(*weight_shape),
        "weight": 0.01 * np.random.randn(*weight_shape),
        "bias": 0.01 * np.random.randn(output_size)
    }

def get_golden() -> dict[str, np.ndarray]:
    """Generate golden data for test."""
    output_random = np.random.rand(2, 2, 32)
    bias_random = np.random.rand(32)
    return {
        "output_random": output_random,
        "bias_random": bias_random
    }
def get_gpu_datas() -> dict[str, np.ndarray]:
    """Generate gpu data for test."""
    output_random = np.random.rand(2, 2, 32)
    bias_random = np.random.rand(32)
    return {
        "output_random": output_random,
        "bias_random": bias_random
    }

GOLDEN_DATA = get_golden()
GPU_DATA = get_gpu_datas()
