




# Copyright 2022 The HuggingFace Team and The OpenBMB Team. 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 typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase_		:				str									=     {
    "configuration_cpmant": ["CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP", "CpmAntConfig"],
    "tokenization_cpmant": ["CpmAntTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_		:				Dict									=     [
							    "CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "CpmAntForCausalLM",
							    "CpmAntModel",
							    "CpmAntPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
							from .tokenization_cpmant import CpmAntTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_cpmant import (
														    CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CpmAntForCausalLM,
														    CpmAntModel,
														    CpmAntPreTrainedModel,
														)


else:
							import sys

							UpperCAmelCase_		:				Dict									=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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.

# this script dumps information about the environment

import os
import sys

import transformers


UpperCAmelCase_		:				str									=     "3"

print("Python version:", sys.version)
print("transformers version:", transformers.__version__)

try:
							import torch

							print("Torch version:", torch.__version__)
							print("Cuda available:", torch.cuda.is_available())
							print("Cuda version:", torch.version.cuda)
							print("CuDNN version:", torch.backends.cudnn.version())
							print("Number of GPUs available:", torch.cuda.device_count())
							print("NCCL version:", torch.cuda.nccl.version())
except ImportError:
							print("Torch version:", None)

try:
							import deepspeed

							print("DeepSpeed version:", deepspeed.__version__)
except ImportError:
							print("DeepSpeed version:", None)

try:
							import tensorflow as tf

							print("TensorFlow version:", tf.__version__)
							print("TF GPUs available:", bool(tf.config.list_physical_devices("GPU")))
							print("Number of TF GPUs available:", len(tf.config.list_physical_devices("GPU")))
except ImportError:
							print("TensorFlow version:", None)




