# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
# Parts of the code in this file have been adapted from Modulus repo Copyright (c) NVIDIA CORPORATION & AFFILIATES

# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# 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.

from dataclasses import dataclass


@dataclass
class ModelMetaData:
    """Data class for storing essential meta data needed for all Modulus Models"""

    # Model info
    name: str = "ModulusModule"
    # Optimization
    jit: bool = False
    cuda_graphs: bool = False
    amp: bool = False
    amp_cpu: bool = None
    amp_gpu: bool = None
    torch_fx: bool = False
    # Data type
    bf16: bool = False
    # Inference
    onnx: bool = False
    onnx_gpu: bool = None
    onnx_cpu: bool = None
    onnx_runtime: bool = False
    trt: bool = False
    # Physics informed
    var_dim: int = -1
    func_torch: bool = False
    auto_grad: bool = False

    def __post_init__(self):
        self.amp_cpu = self.amp if self.amp_cpu is None else self.amp_cpu
        self.amp_gpu = self.amp if self.amp_gpu is None else self.amp_gpu
        self.onnx_cpu = self.onnx if self.onnx_cpu is None else self.onnx_cpu
        self.onnx_gpu = self.onnx if self.onnx_gpu is None else self.onnx_gpu
