import jax
import jax.numpy as jnp
import numpy as np
import tensorflow as tf
import torch

class ArrayLibraries:
    @staticmethod
    def jax_operations(x):
        # Basic JAX operations
        result = jax.numpy.sum(x)
        result = jax.numpy.mean(x, axis=0)
        result = jax.numpy.max(x)
        return result

    @staticmethod
    def numpy_operations(x):
        # Basic NumPy operations
        result = np.sum(x)
        result = np.mean(x, axis=0)
        result = np.max(x)
        return result

    @staticmethod
    def tensorflow_operations(x):
        # Basic TensorFlow operations
        result = tf.reduce_sum(x)
        result = tf.reduce_mean(x, axis=0)
        result = tf.reduce_max(x)
        return result

    @staticmethod
    def pytorch_operations(x):
        # Basic PyTorch operations
        result = torch.sum(x)
        result = torch.mean(x, dim=0)
        result = torch.max(x)
        return result

    @staticmethod
    def convert_jax_to_numpy(x):
        return np.array(x)

    @staticmethod
    def convert_numpy_to_jax(x):
        return jnp.array(x)

    @staticmethod
    def convert_numpy_to_tensorflow(x):
        return tf.convert_to_tensor(x)

    @staticmethod
    def convert_tensorflow_to_numpy(x):
        return x.numpy()

    @staticmethod
    def convert_numpy_to_pytorch(x):
        return torch.from_numpy(x)

    @staticmethod
    def convert_pytorch_to_numpy(x):
        return x.detach().cpu().numpy()
