



"""simple docstring"""
import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


__a           =							logging.get_logger(__name__)

__a           =							{
    "facebook/musicgen-small": "https://huggingface.co/facebook/musicgen-small/resolve/main/config.json",
    # See all Musicgen models at https://huggingface.co/models?filter=musicgen
}
class 							lowerCamelCase    (     _lowerCAmelCase							):






					'''simple docstring'''





					_A						:     Dict		=	"""musicgen_decoder"""
					_A						:     str		=	["""past_key_values"""]






					def __init__(			self:				List[str]		,	snake_case:				int=2_048		,	snake_case:				Tuple=2_048		,	snake_case:				Any=24		,	snake_case:				Optional[Any]=4_096		,	snake_case:				List[Any]=16		,	snake_case:				int=0.0		,	snake_case:				Dict=True		,	snake_case:				int="gelu"		,	snake_case:				List[Any]=1_024		,	snake_case:				Optional[Any]=0.1		,	snake_case:				List[str]=0.0		,	snake_case:				Optional[int]=0.0		,	snake_case:				int=0.0_2		,	snake_case:				List[Any]=False		,	snake_case:				str=4		,	snake_case:				Union[str, Any]=2_048		,	snake_case:				int=2_048		,	snake_case:				Dict=None		,	snake_case:				Optional[int]=False		,	**snake_case:				Optional[int]		,	)  ->      int:
											snake_case_					:Optional[Any]		=     vocab_size
											snake_case_					:List[Any]		=     max_position_embeddings
											snake_case_					:Optional[Any]		=     hidden_size
											snake_case_					:Optional[Any]		=     ffn_dim
											snake_case_					:Union[str, Any]		=     num_hidden_layers
											snake_case_					:List[str]		=     num_attention_heads
											snake_case_					:Optional[Any]		=     dropout
											snake_case_					:List[str]		=     attention_dropout
											snake_case_					:Any		=     activation_dropout
											snake_case_					:Dict		=     activation_function
											snake_case_					:str		=     initializer_factor
											snake_case_					:Optional[int]		=     layerdrop
											snake_case_					:Union[str, Any]		=     use_cache
											snake_case_					:int		=     scale_embedding  # scale factor will be sqrt(d_model) if True
											snake_case_					:int		=     num_codebooks
											super().__init__(
											    pad_token_id=snake_case		,	bos_token_id=snake_case		,	eos_token_id=snake_case		,	tie_word_embeddings=snake_case		,	**snake_case		,	)

class 							lowerCamelCase    (     _lowerCAmelCase							):






					'''simple docstring'''





					_A						:     List[str]		=	"""musicgen"""
					_A						:     Any		=	True






					def __init__(			self:				Any		,	**snake_case:				Optional[int]		)  ->      Any:
											super().__init__(**snake_case		)
											if "text_encoder" not in kwargs or "audio_encoder" not in kwargs or "decoder" not in kwargs:
																	raise ValueError("""Config has to be initialized with text_encoder, audio_encoder and decoder config"""		)

											snake_case_					:Optional[Any]		=     kwargs.pop("""text_encoder"""		)
											snake_case_					:List[str]		=     text_encoder_config.pop("""model_type"""		)

											snake_case_					:int		=     kwargs.pop("""audio_encoder"""		)
											snake_case_					:Dict		=     audio_encoder_config.pop("""model_type"""		)

											snake_case_					:Tuple		=     kwargs.pop("""decoder"""		)

											snake_case_					:Any		=     AutoConfig.for_model(snake_case		,	**snake_case		)
											snake_case_					:Optional[int]		=     AutoConfig.for_model(snake_case		,	**snake_case		)
											snake_case_					:int		=     MusicgenDecoderConfig(**snake_case		)
											snake_case_					:Optional[Any]		=     True






					@classmethod
					def   lowerCAmelCase_							(			cls:				Dict		,	snake_case:				PretrainedConfig		,	snake_case:				PretrainedConfig		,	snake_case:				MusicgenDecoderConfig		,	**snake_case:				Optional[Any]		,	)  ->      List[Any]:
											return cls(
											    text_encoder=text_encoder_config.to_dict()		,	audio_encoder=audio_encoder_config.to_dict()		,	decoder=decoder_config.to_dict()		,	**snake_case		,	)






					def   lowerCAmelCase_							(			self:				str		)  ->      Optional[Any]:
											snake_case_					:List[str]		=     copy.deepcopy(self.__dict__		)
											snake_case_					:Optional[int]		=     self.text_encoder.to_dict()
											snake_case_					:Union[str, Any]		=     self.audio_encoder.to_dict()
											snake_case_					:Optional[int]		=     self.decoder.to_dict()
											snake_case_					:Dict		=     self.__class__.model_type
											return output





"""simple docstring"""
import colorsys
import io

import cva
import matplotlib as mpl
import matplotlib.colors as mplc
import matplotlib.figure as mplfigure
import numpy as np
import torch
from matplotlib.backends.backend_agg import FigureCanvasAgg

from utils import img_tensorize


__a           =							10_00
class 							lowerCamelCase    :






					'''simple docstring'''





					def __init__(			self:				Dict		,	snake_case:				List[str]		,	snake_case:				Optional[int]=1.2		,	snake_case:				List[Any]="g"		,	snake_case:				Dict=0.5		,	snake_case:				Dict="-"		,	snake_case:				Tuple="test_out.jpg"		,	snake_case:				List[str]=True		,	snake_case:				List[Any]=False		,	snake_case:				List[str]=None		,	snake_case:				int=None		,	snake_case:				Tuple=0.7		,	)  ->      Optional[int]:
											if isinstance(snake_case		,	torch.Tensor		):
																	snake_case_					:Union[str, Any]		=     img.numpy().astype("""np.uint8"""		)
											if isinstance(snake_case		,	snake_case		):
																	snake_case_					:Optional[Any]		=     img_tensorize(snake_case		)
											assert isinstance(snake_case		,	np.ndarray		)

											snake_case_,			snake_case_					:Dict		=     img.shape[1], img.shape[0]
											snake_case_					:List[Any]		=     mplfigure.Figure(frameon=snake_case		)
											snake_case_					:Any		=     fig.get_dpi()
											snake_case_					:Tuple		=     (width * scale + 1E-2) / dpi
											snake_case_					:Any		=     (height * scale + 1E-2) / dpi
											fig.set_size_inches(snake_case		,	snake_case		)
											snake_case_					:str		=     fig.add_axes([0.0, 0.0, 1.0, 1.0]		)
											ax.axis("""off"""		)
											ax.set_xlim(0.0		,	snake_case		)
											ax.set_ylim(snake_case		)

											snake_case_					:str		=     saveas
											snake_case_					:str		=     rgb
											snake_case_					:Any		=     pynb
											snake_case_					:List[str]		=     img
											snake_case_					:Dict		=     edgecolor
											snake_case_					:Any		=     0.5
											snake_case_					:Dict		=     linestyle
											snake_case_					:Optional[Any]		=     int(np.sqrt(min(snake_case		,	snake_case		)		) * scale // 3		)
											snake_case_					:Optional[Any]		=     width
											snake_case_					:List[str]		=     height
											snake_case_					:int		=     scale
											snake_case_					:Tuple		=     fig
											snake_case_					:Any		=     ax
											snake_case_					:Union[str, Any]		=     pad
											snake_case_					:Dict		=     idaobj
											snake_case_					:Any		=     idaattr
											snake_case_					:Any		=     FigureCanvasAgg(snake_case		)






					def   lowerCAmelCase_							(			self:				int		,	snake_case:				Dict		,	snake_case:				Any=None		)  ->      List[str]:
											if color is None:
																	snake_case_					:Any		=     self.edgecolor
											((snake_case_),			(snake_case_),			(snake_case_),			(snake_case_))					:List[Any]		=     box
											snake_case_					:Union[str, Any]		=     xa - xa
											snake_case_					:Dict		=     ya - ya
											self.ax.add_patch(
											    mpl.patches.Rectangle(
											        (xa, ya)		,	snake_case		,	snake_case		,	fill=snake_case		,	edgecolor=snake_case		,	linewidth=self.font_size // 3		,	alpha=self.alpha		,	linestyle=self.linestyle		,	)		)






					def   lowerCAmelCase_							(			self:				Dict		,	snake_case:				Union[str, Any]		,	snake_case:				Union[str, Any]=None		,	snake_case:				Any=None		,	snake_case:				List[str]=None		,	snake_case:				int=None		)  ->      Any:
											if len(boxes.shape		) > 2:
																	snake_case_					:str		=     boxes[0]
											if len(obj_ids.shape		) > 1:
																	snake_case_					:Optional[int]		=     obj_ids[0]
											if len(obj_scores.shape		) > 1:
																	snake_case_					:Union[str, Any]		=     obj_scores[0]
											if len(attr_ids.shape		) > 1:
																	snake_case_					:Union[str, Any]		=     attr_ids[0]
											if len(attr_scores.shape		) > 1:
																	snake_case_					:Optional[int]		=     attr_scores[0]
											if isinstance(snake_case		,	torch.Tensor		):
																	snake_case_					:str		=     boxes.numpy()
											if isinstance(snake_case		,	snake_case		):
																	snake_case_					:List[str]		=     np.array(snake_case		)
											assert isinstance(snake_case		,	np.ndarray		)
											snake_case_					:Optional[int]		=     np.prod(boxes[:, 2:] - boxes[:, :2]		,	axis=1		)
											snake_case_					:Optional[int]		=     np.argsort(-areas		).tolist()
											snake_case_					:int		=     boxes[sorted_idxs] if boxes is not None else None
											snake_case_					:Optional[int]		=     obj_ids[sorted_idxs] if obj_ids is not None else None
											snake_case_					:int		=     obj_scores[sorted_idxs] if obj_scores is not None else None
											snake_case_					:str		=     attr_ids[sorted_idxs] if attr_ids is not None else None
											snake_case_					:Any		=     attr_scores[sorted_idxs] if attr_scores is not None else None

											snake_case_					:Union[str, Any]		=     [self._random_color(maximum=1		) for _ in range(len(snake_case		)		)]
											snake_case_					:List[Any]		=     [assigned_colors[idx] for idx in sorted_idxs]
											if obj_ids is not None:
																	snake_case_					:Optional[int]		=     self._create_text_labels_attr(snake_case		,	snake_case		,	snake_case		,	snake_case		)
																	for i in range(len(snake_case		)		):
																							snake_case_					:Any		=     assigned_colors[i]
																							self.add_box(boxes[i]		,	snake_case		)
																							self.draw_labels(labels[i]		,	boxes[i]		,	snake_case		)






					def   lowerCAmelCase_							(			self:				Any		,	snake_case:				Dict		,	snake_case:				str		,	snake_case:				Any		)  ->      Union[str, Any]:
											snake_case_,			snake_case_,			snake_case_,			snake_case_					:Optional[int]		=     box
											snake_case_					:Dict		=     (xa, ya)
											snake_case_					:Union[str, Any]		=     (ya - ya) * (xa - xa)
											snake_case_					:Optional[Any]		=     _SMALL_OBJ * self.scale
											if instance_area < small or ya - ya < 40 * self.scale:
																	if ya >= self.height - 5:
																							snake_case_					:str		=     (xa, ya)
																	else:
																							snake_case_					:Any		=     (xa, ya)

											snake_case_					:Optional[Any]		=     (ya - ya) / np.sqrt(self.height * self.width		)
											snake_case_					:Dict		=     self._change_color_brightness(snake_case		,	brightness_factor=0.7		)
											snake_case_					:List[Any]		=     np.clip((height_ratio - 0.0_2) / 0.0_8 + 1		,	1.2		,	2		)
											font_size *= 0.7_5 * self.font_size

											self.draw_text(
											    text=snake_case		,	position=snake_case		,	color=snake_case		,	)






					def   lowerCAmelCase_							(			self:				List[str]		,	snake_case:				Union[str, Any]		,	snake_case:				Optional[int]		,	snake_case:				Union[str, Any]="g"		,	snake_case:				Tuple="left"		,	)  ->      str:
											snake_case_					:Optional[Any]		=     0
											snake_case_					:Union[str, Any]		=     self.font_size
											snake_case_					:Any		=     np.maximum(list(mplc.to_rgb(snake_case		)		)		,	0.2		)
											snake_case_					:Optional[Any]		=     max(0.8		,	np.max(snake_case		)		)
											snake_case_					:List[str]		=     {
											    """facecolor""": """black""",
											    """alpha""": self.alpha,
											    """pad""": self.pad,
											    """edgecolor""": """none""",
											}
											snake_case_,			snake_case_					:Optional[int]		=     position
											self.ax.text(
											    snake_case		,	snake_case		,	snake_case		,	size=font_size * self.scale		,	family="""sans-serif"""		,	bbox=snake_case		,	verticalalignment="""top"""		,	horizontalalignment=snake_case		,	color=snake_case		,	zorder=10		,	rotation=snake_case		,	)






					def   lowerCAmelCase_							(			self:				Union[str, Any]		,	snake_case:				Tuple=None		)  ->      Dict:
											if saveas is None:
																	snake_case_					:int		=     self.saveas
											if saveas.lower().endswith(""".jpg"""		) or saveas.lower().endswith(""".png"""		):
																	cva.imwrite(
																	    snake_case		,	self._get_buffer()[:, :, ::-1]		,	)
											else:
																	self.fig.savefig(snake_case		)






					def   lowerCAmelCase_							(			self:				str		,	snake_case:				List[Any]		,	snake_case:				Dict		,	snake_case:				Any		,	snake_case:				Tuple		)  ->      Dict:
											snake_case_					:int		=     [self.idaobj[i] for i in classes]
											snake_case_					:List[str]		=     [self.idaattr[i] for i in attr_classes]
											snake_case_					:List[str]		=     [
											    f"""{label} {score:.2f} {attr} {attr_score:.2f}"""
											    for label, score, attr, attr_score in zip(snake_case		,	snake_case		,	snake_case		,	snake_case		)
											]
											return labels






					def   lowerCAmelCase_							(			self:				Dict		,	snake_case:				Any		,	snake_case:				Dict		)  ->      Tuple:
											snake_case_					:Union[str, Any]		=     [self.idaobj[i] for i in classes]
											if scores is not None:
																	if labels is None:
																							snake_case_					:List[Any]		=     ["""{:.0f}%""".format(s * 100		) for s in scores]
																	else:
																							snake_case_					:Tuple		=     ["""{} {:.0f}%""".format(snake_case		,	s * 100		) for li, s in zip(snake_case		,	snake_case		)]
											return labels






					def   lowerCAmelCase_							(			self:				str		,	snake_case:				str=255		)  ->      List[str]:
											snake_case_					:Optional[Any]		=     np.random.randint(0		,	len(_COLORS		)		)
											snake_case_					:int		=     _COLORS[idx] * maximum
											if not self.rgb:
																	snake_case_					:List[Any]		=     ret[::-1]
											return ret






					def   lowerCAmelCase_							(			self:				Optional[int]		)  ->      Union[str, Any]:
											if not self.pynb:
																	snake_case_,			snake_case_					:str		=     self.canvas.print_to_buffer()
																	if (width, height) != (self.width, self.height):
																							snake_case_					:Optional[int]		=     cva.resize(self.img		,	(width, height)		)
																	else:
																							snake_case_					:List[Any]		=     self.img
											else:
																	snake_case_					:List[Any]		=     io.BytesIO()  # works for cairo backend
																	self.canvas.print_rgba(snake_case		)
																	snake_case_,			snake_case_					:Tuple		=     self.width, self.height
																	snake_case_					:Any		=     buf.getvalue()
																	snake_case_					:List[str]		=     self.img

											snake_case_					:Optional[int]		=     np.frombuffer(snake_case		,	dtype="""uint8"""		)
											snake_case_					:Optional[Any]		=     buffer.reshape(snake_case		,	snake_case		,	4		)
											snake_case_,			snake_case_					:Tuple		=     np.split(snake_case		,	[3]		,	axis=2		)

											try:
																	import numexpr as ne  # fuse them with numexpr

																	snake_case_					:Any		=     ne.evaluate("""img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)"""		)
											except ImportError:
																	snake_case_					:Union[str, Any]		=     alpha.astype("""float32"""		) / 2_5_5.0
																	snake_case_					:int		=     img * (1 - alpha) + rgb * alpha

											return visualized_image.astype("""uint8"""		)






					def   lowerCAmelCase_							(			self:				Optional[Any]		,	snake_case:				int		,	snake_case:				Optional[Any]		)  ->      Tuple:
											assert brightness_factor >= -1.0 and brightness_factor <= 1.0
											snake_case_					:int		=     mplc.to_rgb(snake_case		)
											snake_case_					:List[Any]		=     colorsys.rgb_to_hls(*mplc.to_rgb(snake_case		)		)
											snake_case_					:Optional[Any]		=     polygon_color[1] + (brightness_factor * polygon_color[1])
											snake_case_					:List[str]		=     0.0 if modified_lightness < 0.0 else modified_lightness
											snake_case_					:Dict		=     1.0 if modified_lightness > 1.0 else modified_lightness
											snake_case_					:int		=     colorsys.hls_to_rgb(polygon_color[0]		,	snake_case		,	polygon_color[2]		)
											return modified_color

__a           =							(
    np.array(
        [
            0.0_00,
            0.4_47,
            0.7_41,
            0.8_50,
            0.3_25,
            0.0_98,
            0.9_29,
            0.6_94,
            0.1_25,
            0.4_94,
            0.1_84,
            0.5_56,
            0.4_66,
            0.6_74,
            0.1_88,
            0.3_01,
            0.7_45,
            0.9_33,
            0.6_35,
            0.0_78,
            0.1_84,
            0.3_00,
            0.3_00,
            0.3_00,
            0.6_00,
            0.6_00,
            0.6_00,
            1.0_00,
            0.0_00,
            0.0_00,
            1.0_00,
            0.5_00,
            0.0_00,
            0.7_49,
            0.7_49,
            0.0_00,
            0.0_00,
            1.0_00,
            0.0_00,
            0.0_00,
            0.0_00,
            1.0_00,
            0.6_67,
            0.0_00,
            1.0_00,
            0.3_33,
            0.3_33,
            0.0_00,
            0.3_33,
            0.6_67,
            0.0_00,
            0.3_33,
            1.0_00,
            0.0_00,
            0.6_67,
            0.3_33,
            0.0_00,
            0.6_67,
            0.6_67,
            0.0_00,
            0.6_67,
            1.0_00,
            0.0_00,
            1.0_00,
            0.3_33,
            0.0_00,
            1.0_00,
            0.6_67,
            0.0_00,
            1.0_00,
            1.0_00,
            0.0_00,
            0.0_00,
            0.3_33,
            0.5_00,
            0.0_00,
            0.6_67,
            0.5_00,
            0.0_00,
            1.0_00,
            0.5_00,
            0.3_33,
            0.0_00,
            0.5_00,
            0.3_33,
            0.3_33,
            0.5_00,
            0.3_33,
            0.6_67,
            0.5_00,
            0.3_33,
            1.0_00,
            0.5_00,
            0.6_67,
            0.0_00,
            0.5_00,
            0.6_67,
            0.3_33,
            0.5_00,
            0.6_67,
            0.6_67,
            0.5_00,
            0.6_67,
            1.0_00,
            0.5_00,
            1.0_00,
            0.0_00,
            0.5_00,
            1.0_00,
            0.3_33,
            0.5_00,
            1.0_00,
            0.6_67,
            0.5_00,
            1.0_00,
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    .astype(np.floataa)
    .reshape(-1, 3)
)
