


"""simple docstring"""
import re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


__SCREAMING_SNAKE_CASE							:      str						=      logging.get_logger(__name__)







def   _a			( _SCREAMING_SNAKE_CASE			)      ->			str:
							snake_case_          =						r"\w+[.]\d+"
							snake_case_          =						re.findall(__lowerCamelCase			,	__lowerCamelCase			)
							for pat in pats:
														snake_case_          =						key.replace(__lowerCamelCase			,	"""_""".join(pat.split("""."""			)			)			)
							return key







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			List[Any]:
							snake_case_          =						pt_tuple_key[:-1] + ("scale",)
							if (
							    any("""norm""" in str_ for str_ in pt_tuple_key			)
							    and (pt_tuple_key[-1] == "bias")
							    and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
							    and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
							):
														snake_case_          =						pt_tuple_key[:-1] + ("scale",)
														return renamed_pt_tuple_key, pt_tensor
							elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
														snake_case_          =						pt_tuple_key[:-1] + ("scale",)
														return renamed_pt_tuple_key, pt_tensor

							# embedding
							if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
														snake_case_          =						pt_tuple_key[:-1] + ("embedding",)
														return renamed_pt_tuple_key, pt_tensor

							# conv layer
							snake_case_          =						pt_tuple_key[:-1] + ("kernel",)
							if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
														snake_case_          =						pt_tensor.transpose(2			,	3			,	1			,	0			)
														return renamed_pt_tuple_key, pt_tensor

							# linear layer
							snake_case_          =						pt_tuple_key[:-1] + ("kernel",)
							if pt_tuple_key[-1] == "weight":
														snake_case_          =						pt_tensor.T
														return renamed_pt_tuple_key, pt_tensor

							# old PyTorch layer norm weight
							snake_case_          =						pt_tuple_key[:-1] + ("weight",)
							if pt_tuple_key[-1] == "gamma":
														return renamed_pt_tuple_key, pt_tensor

							# old PyTorch layer norm bias
							snake_case_          =						pt_tuple_key[:-1] + ("bias",)
							if pt_tuple_key[-1] == "beta":
														return renamed_pt_tuple_key, pt_tensor

							return pt_tuple_key, pt_tensor







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE=42			)      ->			str:
							# Step 1: Convert pytorch tensor to numpy
							snake_case_          =						{k: v.numpy() for k, v in pt_state_dict.items()}

							# Step 2: Since the model is stateless, get random Flax params
							snake_case_          =						flax_model.init_weights(PRNGKey(__lowerCamelCase			)			)

							snake_case_          =						flatten_dict(__lowerCamelCase			)
							snake_case_          =						{}

							# Need to change some parameters name to match Flax names
							for pt_key, pt_tensor in pt_state_dict.items():
														snake_case_          =						rename_key(__lowerCamelCase			)
														snake_case_          =						tuple(renamed_pt_key.split("""."""			)			)

														# Correctly rename weight parameters
														snake_case_          =						rename_key_and_reshape_tensor(__lowerCamelCase			,	__lowerCamelCase			,	__lowerCamelCase			)

														if flax_key in random_flax_state_dict:
																					if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
																												raise ValueError(
																												    f"""PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape """
																												    f"""{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}."""			)

        # also add unexpected weight so that warning is thrown
														snake_case_          =						jnp.asarray(__lowerCamelCase			)

							return unflatten_dict(__lowerCamelCase			)







"""simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    'stable diffusion controlnet',
    '0.22.0',
    'Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import FlaxStableDiffusionControlNetPipeline` instead.',
    standard_warn=False,
    stacklevel=3,
)



