

"""simple docstring"""
import operator as op


_A							=  "scaler.pt"
_A							=  "pytorch_model"
_A							=  "random_states"
_A							=  "optimizer"
_A							=  "scheduler"
_A							=  "pytorch_model.bin"
_A							=  "pytorch_model.bin.index.json"
_A							=  "model.safetensors"
_A							=  "model.safetensors.index.json"
_A							=  "1.10.2"
_A							=  "py38"
_A							=  "4.17.0"
_A							=  ["ml.p3.16xlarge", "ml.p3dn.24xlarge", "ml.p4dn.24xlarge"]
_A							=  ["FULL_SHARD", "SHARD_GRAD_OP", "NO_SHARD", "HYBRID_SHARD", "HYBRID_SHARD_ZERO2"]
_A							=  ["TRANSFORMER_BASED_WRAP", "SIZE_BASED_WRAP", "NO_WRAP"]
_A							=  ["BACKWARD_PRE", "BACKWARD_POST", "NO_PREFETCH"]
_A							=  ["FULL_STATE_DICT", "LOCAL_STATE_DICT", "SHARDED_STATE_DICT"]
_A							=  "2.0.1"
_A							=  ["pdsh", "standard", "openmpi", "mvapich"]
_A							=  ["default", "reduce-overhead", "max-autotune"]

_A							=  {">": op.gt, ">=": op.ge, "==": op.eq, "!=": op.ne, "<=": op.le, "<": op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
_A							=  [
    "nnodes",
    "nproc_per_node",
    "rdzv_backend",
    "rdzv_endpoint",
    "rdzv_id",
    "rdzv_conf",
    "standalone",
    "max_restarts",
    "monitor_interval",
    "start_method",
    "role",
    "module",
    "m",
    "no_python",
    "run_path",
    "log_dir",
    "r",
    "redirects",
    "t",
    "tee",
    "node_rank",
    "master_addr",
    "master_port",
]

_A							=  ["DEEPSPEED", "MULTI_GPU", "FSDP", "MEGATRON_LM"]
_A							=  ["DEEPSPEED", "MULTI_XPU", "FSDP"]







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


SCREAMING_SNAKE_CASE__     :     str		    =       {
    "configuration_altclip": [
        "ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "AltCLIPConfig",
        "AltCLIPTextConfig",
        "AltCLIPVisionConfig",
    ],
    "processing_altclip": ["AltCLIPProcessor"],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				SCREAMING_SNAKE_CASE__     :     Any		    =       [
				    "ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "AltCLIPPreTrainedModel",
				    "AltCLIPModel",
				    "AltCLIPTextModel",
				    "AltCLIPVisionModel",
				]


if TYPE_CHECKING:
				from .configuration_altclip import (
				    ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    AltCLIPConfig,
				    AltCLIPTextConfig,
				    AltCLIPVisionConfig,
				)
				from .processing_altclip import AltCLIPProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_altclip import (
								    ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    AltCLIPModel,
								    AltCLIPPreTrainedModel,
								    AltCLIPTextModel,
								    AltCLIPVisionModel,
								)


else:
				import sys

				SCREAMING_SNAKE_CASE__     :     Tuple		    =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
