
import argparse
import json
from pathlib import Path

import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image

from transformers import (
    SwiftFormerConfig,
    SwiftFormerForImageClassification,
    ViTImageProcessor,
)
from transformers.utils import logging


logging.set_verbosity_info()
lowercase__		:Optional[int]   =    logging.get_logger(__name__)

lowercase__		:Union[str, Any]   =    torch.device("cpu")



def        UpperCamelCase    (							):
					'''simple docstring'''
					lowercase							=						'''http://images.cocodataset.org/val2017/000000039769.jpg'''
					lowercase							=						Image.open(requests.get(lowerCAmelCase__ ,			stream=lowerCAmelCase__		).raw		)
					return im



def        UpperCamelCase    (							lowerCAmelCase__		):
					'''simple docstring'''
					if swiftformer_name == "swiftformer_xs":
										return torch.tensor([-2.1703E00, 2.1107E00, -2.0811E00, 8.8685E-01, 2.4360E-01]		)

					elif swiftformer_name == "swiftformer_s":
										return torch.tensor([3.9636E-01, 2.3478E-01, -1.6963E00, -1.7381E00, -8.6337E-01]		)

					elif swiftformer_name == "swiftformer_l1":
										return torch.tensor([-4.2768E-01, -4.7429E-01, -1.0897E00, -1.0248E00, 3.5523E-02]		)

					elif swiftformer_name == "swiftformer_l3":
										return torch.tensor([-2.5330E-01, 2.4211E-01, -6.0185E-01, -8.2789E-01, -6.0446E-02]		)



def        UpperCamelCase    (							lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		):
					'''simple docstring'''
					lowercase							=						dct.pop(lowerCAmelCase__		)
					lowercase							=						val



def        UpperCamelCase    (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase							=						[]
					for k in state_dict.keys():
										lowercase							=						k
										if ".pwconv" in k:
															lowercase							=						k_new.replace('''.pwconv''' ,			'''.point_wise_conv'''		)
										if ".dwconv" in k:
															lowercase							=						k_new.replace('''.dwconv''' ,			'''.depth_wise_conv'''		)
										if ".Proj." in k:
															lowercase							=						k_new.replace('''.Proj.''' ,			'''.proj.'''		)
										if "patch_embed" in k_new:
															lowercase							=						k_new.replace('''patch_embed''' ,			'''swiftformer.patch_embed.patch_embedding'''		)
										if "network" in k_new:
															lowercase							=						k_new.split('''.'''		)
															if ls[2].isdigit():
																				lowercase							=						'''swiftformer.encoder.network.''' + ls[1] + '''.blocks.''' + ls[2] + '''.''' + '''.'''.join(ls[3:]		)
															else:
																				lowercase							=						k_new.replace('''network''' ,			'''swiftformer.encoder.network'''		)
										rename_keys.append((k, k_new)		)
					return rename_keys



@torch.no_grad()
def        UpperCamelCase    (							lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		):
					'''simple docstring'''
					lowercase							=						SwiftFormerConfig()

					# dataset (ImageNet-21k only or also fine-tuned on ImageNet 2012), patch_size and image_size
					lowercase							=						1000
					lowercase							=						'''huggingface/label-files'''
					lowercase							=						'''imagenet-1k-id2label.json'''
					lowercase							=						json.load(open(hf_hub_download(lowerCAmelCase__ ,			lowerCAmelCase__ ,			repo_type='''dataset'''		) ,			'''r'''		)		)
					lowercase							=						{int(lowerCAmelCase__		): v for k, v in idalabel.items()}
					lowercase							=						idalabel
					lowercase							=						{v: k for k, v in idalabel.items()}

					# size of the architecture
					if swiftformer_name == "swiftformer_xs":
										lowercase							=						[3, 3, 6, 4]
										lowercase							=						[48, 56, 112, 220]

					elif swiftformer_name == "swiftformer_s":
										lowercase							=						[3, 3, 9, 6]
										lowercase							=						[48, 64, 168, 224]

					elif swiftformer_name == "swiftformer_l1":
										lowercase							=						[4, 3, 10, 5]
										lowercase							=						[48, 96, 192, 384]

					elif swiftformer_name == "swiftformer_l3":
										lowercase							=						[4, 4, 12, 6]
										lowercase							=						[64, 128, 320, 512]

					# load state_dict of original model, remove and rename some keys
					if original_ckpt:
										if original_ckpt.startswith('''https'''		):
															lowercase							=						torch.hub.load_state_dict_from_url(lowerCAmelCase__ ,			map_location='''cpu''' ,			check_hash=lowerCAmelCase__		)
										else:
															lowercase							=						torch.load(lowerCAmelCase__ ,			map_location='''cpu'''		)
					lowercase							=						checkpoint

					lowercase							=						create_rename_keys(lowerCAmelCase__		)
					for rename_key_src, rename_key_dest in rename_keys:
										rename_key(lowerCAmelCase__ ,			lowerCAmelCase__ ,			lowerCAmelCase__		)

					# load HuggingFace model
					lowercase							=						SwiftFormerForImageClassification(lowerCAmelCase__		).eval()
					hf_model.load_state_dict(lowerCAmelCase__		)

					# prepare test inputs
					lowercase							=						prepare_img()
					lowercase							=						ViTImageProcessor.from_pretrained('''preprocessor_config'''		)
					lowercase							=						processor(images=lowerCAmelCase__ ,			return_tensors='''pt'''		)

					# compare outputs from both models
					lowercase							=						get_expected_output(lowerCAmelCase__		)
					lowercase							=						hf_model(inputs['''pixel_values''']		).logits

					assert hf_logits.shape == torch.Size([1, 1000]		)
					assert torch.allclose(hf_logits[0, 0:5] ,			lowerCAmelCase__ ,			atol=1E-3		)

					Path(lowerCAmelCase__		).mkdir(exist_ok=lowerCAmelCase__		)
					print(f'Saving model {swiftformer_name} to {pytorch_dump_folder_path}'		)
					hf_model.save_pretrained(lowerCAmelCase__		)


if __name__ == "__main__":
							lowercase__		:Union[str, Any]   =    argparse.ArgumentParser()
							# Required parameters
							parser.add_argument(
							    "--swiftformer_name",
							    default="swiftformer_xs",
							    choices=["swiftformer_xs", "swiftformer_s", "swiftformer_l1", "swiftformer_l3"],
							    type=str,
							    help="Name of the SwiftFormer model you'd like to convert.",
							)
							parser.add_argument(
							    "--pytorch_dump_folder_path",
							    default="./converted_outputs/",
							    type=str,
							    help="Path to the output PyTorch model directory.",
							)
							parser.add_argument("--original_ckpt", default=None, type=str, help="Path to the original model checkpoint.")

							lowercase__		:Dict   =    parser.parse_args()
							convert_swiftformer_checkpoint(args.swiftformer_name, args.pytorch_dump_folder_path, args.original_ckpt)






import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pytest

from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex

from .utils import require_elasticsearch, require_faiss


lowercase__		:Optional[int]   =    pytest.mark.integration







@require_faiss
class 				lowercase		(					SCREAMING_SNAKE_CASE__		):




							def  A__      (				self):
												lowercase							=						Dataset.from_dict({'''filename''': ['''my_name-train''' + '''_''' + str(A__) for x in np.arange(3_0).tolist()]})
												return dset




							def  A__      (				self):
												import faiss

												lowercase							=						self._create_dummy_dataset()
												lowercase							=						dset.map(
												    lambda A__   ,A__: {"vecs": i * np.ones(5   ,dtype=np.floataa)}   ,with_indices=A__   ,keep_in_memory=A__)
												lowercase							=						dset.add_faiss_index('''vecs'''   ,batch_size=1_0_0   ,metric_type=faiss.METRIC_INNER_PRODUCT)
												lowercase	,						lowercase							=						dset.get_nearest_examples('''vecs'''   ,np.ones(5   ,dtype=np.floataa))
												self.assertEqual(examples['''filename'''][0]   ,'''my_name-train_29''')
												dset.drop_index('''vecs''')




							def  A__      (				self):
												import faiss

												lowercase							=						self._create_dummy_dataset()
												dset.add_faiss_index_from_external_arrays(
												    external_arrays=np.ones((3_0, 5)) * np.arange(3_0).reshape(-1   ,1)   ,index_name='''vecs'''   ,batch_size=1_0_0   ,metric_type=faiss.METRIC_INNER_PRODUCT   ,)
												lowercase	,						lowercase							=						dset.get_nearest_examples('''vecs'''   ,np.ones(5   ,dtype=np.floataa))
												self.assertEqual(examples['''filename'''][0]   ,'''my_name-train_29''')




							def  A__      (				self):
												import faiss

												lowercase							=						self._create_dummy_dataset()
												dset.add_faiss_index_from_external_arrays(
												    external_arrays=np.ones((3_0, 5)) * np.arange(3_0).reshape(-1   ,1)   ,index_name='''vecs'''   ,metric_type=faiss.METRIC_INNER_PRODUCT   ,)

												# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
												# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
												# see https://bugs.python.org/issue14243 and
												# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
												with tempfile.NamedTemporaryFile(delete=A__) as tmp_file:
																	dset.save_faiss_index('''vecs'''   ,tmp_file.name)
																	dset.load_faiss_index('''vecs2'''   ,tmp_file.name)
												os.unlink(tmp_file.name)

												lowercase	,						lowercase							=						dset.get_nearest_examples('''vecs2'''   ,np.ones(5   ,dtype=np.floataa))
												self.assertEqual(examples['''filename'''][0]   ,'''my_name-train_29''')




							def  A__      (				self):
												lowercase							=						self._create_dummy_dataset()
												dset.add_faiss_index_from_external_arrays(
												    external_arrays=np.ones((3_0, 5)) * np.arange(3_0).reshape(-1   ,1)   ,index_name='''vecs''')
												dset.drop_index('''vecs''')
												self.assertRaises(A__   ,partial(dset.get_nearest_examples   ,'''vecs2'''   ,np.ones(5   ,dtype=np.floataa)))





							def  A__      (				self):
												from elasticsearch import Elasticsearch

												lowercase							=						self._create_dummy_dataset()
												with patch('''elasticsearch.Elasticsearch.search''') as mocked_search, patch(
												    '''elasticsearch.client.IndicesClient.create''') as mocked_index_create, patch('''elasticsearch.helpers.streaming_bulk''') as mocked_bulk:
																	lowercase							=						{'''acknowledged''': True}
																	mocked_bulk.return_value([(True, None)] * 3_0)
																	lowercase							=						{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 2_9}]}}
																	lowercase							=						Elasticsearch()

																	dset.add_elasticsearch_index('''filename'''   ,es_client=A__)
																	lowercase	,						lowercase							=						dset.get_nearest_examples('''filename'''   ,'''my_name-train_29''')
																	self.assertEqual(examples['''filename'''][0]   ,'''my_name-train_29''')







@require_faiss
class 				lowercase		(					SCREAMING_SNAKE_CASE__		):




							def  A__      (				self):
												import faiss

												lowercase							=						FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT)

												# add vectors
												index.add_vectors(np.eye(5   ,dtype=np.floataa))
												self.assertIsNotNone(index.faiss_index)
												self.assertEqual(index.faiss_index.ntotal   ,5)
												index.add_vectors(np.zeros((5, 5)   ,dtype=np.floataa))
												self.assertEqual(index.faiss_index.ntotal   ,1_0)

												# single query
												lowercase							=						np.zeros(5   ,dtype=np.floataa)
												lowercase							=						1
												lowercase	,						lowercase							=						index.search(A__)
												self.assertRaises(A__   ,index.search   ,query.reshape(-1   ,1))
												self.assertGreater(scores[0]   ,0)
												self.assertEqual(indices[0]   ,1)

												# batched queries
												lowercase							=						np.eye(5   ,dtype=np.floataa)[::-1]
												lowercase	,						lowercase							=						index.search_batch(A__)
												self.assertRaises(A__   ,index.search_batch   ,queries[0])
												lowercase							=						[scores[0] for scores in total_scores]
												lowercase							=						[indices[0] for indices in total_indices]
												self.assertGreater(np.min(A__)   ,0)
												self.assertListEqual([4, 3, 2, 1, 0]   ,A__)




							def  A__      (				self):
												import faiss

												lowercase							=						FaissIndex(string_factory='''Flat''')
												index.add_vectors(np.eye(5   ,dtype=np.floataa))
												self.assertIsInstance(index.faiss_index   ,faiss.IndexFlat)
												lowercase							=						FaissIndex(string_factory='''LSH''')
												index.add_vectors(np.eye(5   ,dtype=np.floataa))
												self.assertIsInstance(index.faiss_index   ,faiss.IndexLSH)
												with self.assertRaises(A__):
																	lowercase							=						FaissIndex(string_factory='''Flat'''   ,custom_index=faiss.IndexFlat(5))




							def  A__      (				self):
												import faiss

												lowercase							=						faiss.IndexFlat(5)
												lowercase							=						FaissIndex(custom_index=A__)
												index.add_vectors(np.eye(5   ,dtype=np.floataa))
												self.assertIsInstance(index.faiss_index   ,faiss.IndexFlat)





							def  A__      (				self):
												import faiss

												lowercase							=						FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT)
												index.add_vectors(np.eye(5   ,dtype=np.floataa))

												# Setting delete=False and unlinking manually is not pretty... but it is required on Windows to
												# ensure somewhat stable behaviour. If we don't, we get PermissionErrors. This is an age-old issue.
												# see https://bugs.python.org/issue14243 and
												# https://stackoverflow.com/questions/23212435/permission-denied-to-write-to-my-temporary-file/23212515
												with tempfile.NamedTemporaryFile(delete=A__) as tmp_file:
																	index.save(tmp_file.name)
																	lowercase							=						FaissIndex.load(tmp_file.name)
												os.unlink(tmp_file.name)

												lowercase							=						np.zeros(5   ,dtype=np.floataa)
												lowercase							=						1
												lowercase	,						lowercase							=						index.search(A__)
												self.assertGreater(scores[0]   ,0)
												self.assertEqual(indices[0]   ,1)



@require_faiss
def        UpperCamelCase    (							lowerCAmelCase__		):
					'''simple docstring'''
					import faiss

					lowercase							=						FaissIndex(metric_type=faiss.METRIC_INNER_PRODUCT		)
					index.add_vectors(np.eye(5 ,			dtype=np.floataa		)		)

					lowercase							=						'''index.faiss'''
					lowercase							=						f'mock://{index_name}'
					index.save(lowerCAmelCase__ ,			storage_options=mockfs.storage_options		)
					lowercase							=						FaissIndex.load(lowerCAmelCase__ ,			storage_options=mockfs.storage_options		)

					lowercase							=						np.zeros(5 ,			dtype=np.floataa		)
					lowercase							=						1
					lowercase	,						lowercase							=						index.search(lowerCAmelCase__		)
					assert scores[0] > 0
					assert indices[0] == 1







@require_elasticsearch
class 				lowercase		(					SCREAMING_SNAKE_CASE__		):




							def  A__      (				self):
												from elasticsearch import Elasticsearch

												with patch('''elasticsearch.Elasticsearch.search''') as mocked_search, patch(
												    '''elasticsearch.client.IndicesClient.create''') as mocked_index_create, patch('''elasticsearch.helpers.streaming_bulk''') as mocked_bulk:
																	lowercase							=						Elasticsearch()
																	lowercase							=						{'''acknowledged''': True}
																	lowercase							=						ElasticSearchIndex(es_client=A__)
																	mocked_bulk.return_value([(True, None)] * 3)
																	index.add_documents(['''foo''', '''bar''', '''foobar'''])

																	# single query
																	lowercase							=						'''foo'''
																	lowercase							=						{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 0}]}}
																	lowercase	,						lowercase							=						index.search(A__)
																	self.assertEqual(scores[0]   ,1)
																	self.assertEqual(indices[0]   ,0)

																	# single query with timeout
																	lowercase							=						'''foo'''
																	lowercase							=						{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 0}]}}
																	lowercase	,						lowercase							=						index.search(A__   ,request_timeout=3_0)
																	self.assertEqual(scores[0]   ,1)
																	self.assertEqual(indices[0]   ,0)

																	# batched queries
																	lowercase							=						['''foo''', '''bar''', '''foobar''']
																	lowercase							=						{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 1}]}}
																	lowercase	,						lowercase							=						index.search_batch(A__)
																	lowercase							=						[scores[0] for scores in total_scores]
																	lowercase							=						[indices[0] for indices in total_indices]
																	self.assertGreater(np.min(A__)   ,0)
																	self.assertListEqual([1, 1, 1]   ,A__)

																	# batched queries with timeout
																	lowercase							=						['''foo''', '''bar''', '''foobar''']
																	lowercase							=						{'''hits''': {'''hits''': [{'''_score''': 1, '''_id''': 1}]}}
																	lowercase	,						lowercase							=						index.search_batch(A__   ,request_timeout=3_0)
																	lowercase							=						[scores[0] for scores in total_scores]
																	lowercase							=						[indices[0] for indices in total_indices]
																	self.assertGreater(np.min(A__)   ,0)
																	self.assertListEqual([1, 1, 1]   ,A__)




