




"""simple docstring"""




from typing import TYPE_CHECKING

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


lowerCAmelCase							:			Union[str, Any]     							=							{
    """configuration_trajectory_transformer""": [
        """TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """TrajectoryTransformerConfig""",
    ],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase							:			Optional[Any]     							=							[
					    """TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TrajectoryTransformerModel""",
					    """TrajectoryTransformerPreTrainedModel""",
					    """load_tf_weights_in_trajectory_transformer""",
					]


if TYPE_CHECKING:
					from .configuration_trajectory_transformer import (
					    TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    TrajectoryTransformerConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_trajectory_transformer import (
										    TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TrajectoryTransformerModel,
										    TrajectoryTransformerPreTrainedModel,
										    load_tf_weights_in_trajectory_transformer,
										)


else:
					import sys

					lowerCAmelCase							:			Optional[int]     							=							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









"""simple docstring"""




from math import ceil



def     a__ (				snake_case__       , snake_case__				)						->					Optional[int]:
			lowerCamelCase			      =					list(range(0       , snake_case__				)				)

			lowerCamelCase			      =					[item for sublist in list(device_map.values()				) for item in sublist]

			# Duplicate check
			lowerCamelCase			      =					[]
			for i in device_map_blocks:
						if device_map_blocks.count(snake_case__				) > 1 and i not in duplicate_blocks:
									duplicate_blocks.append(snake_case__				)
    # Missing blocks
			lowerCamelCase			      =					[i for i in blocks if i not in device_map_blocks]
			lowerCamelCase			      =					[i for i in device_map_blocks if i not in blocks]

			if len(snake_case__				) != 0:
						raise ValueError(
						    """Duplicate attention blocks specified in device_map. Attention blocks must be specified to one device."""
						    """ These attention blocks were specified more than once: """ + str(snake_case__				)				)
			if len(snake_case__				) != 0:
						raise ValueError(
						    """There are attention blocks for this model that are not specified in the device_map. Add these attention """
						    """blocks to a device on the device_map: """ + str(snake_case__				)				)
			if len(snake_case__				) != 0:
						raise ValueError(
						    """The device_map contains more attention blocks than this model has. Remove these from the device_map:"""
						    + str(snake_case__				)				)



def     a__ (				snake_case__       , snake_case__				)						->					List[Any]:
			lowerCamelCase			      =					list(range(snake_case__				)				)
			lowerCamelCase			      =					int(ceil(n_layers / len(snake_case__				)				)				)
			lowerCamelCase			      =					[layers[i : i + n_blocks] for i in range(0       , snake_case__       , snake_case__				)]

			return dict(zip(snake_case__       , snake_case__				)				)



