
import argparse
import hashlib
import os
import urllib
import warnings

import torch
from torch import nn
from tqdm import tqdm

from transformers import WhisperConfig, WhisperForConditionalGeneration


UpperCAmelCase	      = {
    '''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3dd57d32accea0b295c96e26691aa14d8822fac7d9d27d5dc00b4ca2826dd03/tiny.en.pt''',
    '''tiny''': '''https://openaipublic.azureedge.net/main/whisper/models/65147644a518d12f04e32d6f3b26facc3f8dd46e5390956a9424a650c0ce22b9/tiny.pt''',
    '''base.en''': '''https://openaipublic.azureedge.net/main/whisper/models/25a8566e1d0c1e2231d1c762132cd20e0f96a85d16145c3a00adf5d1ac670ead/base.en.pt''',
    '''base''': '''https://openaipublic.azureedge.net/main/whisper/models/ed3a0b6b1c0edf879ad9b11b1af5a0e6ab5db9205f891f668f8b0e6c6326e34e/base.pt''',
    '''small.en''': '''https://openaipublic.azureedge.net/main/whisper/models/f953ad0fd29cacd07d5a9eda5624af0f6bcf2258be67c92b79389873d91e0872/small.en.pt''',
    '''small''': '''https://openaipublic.azureedge.net/main/whisper/models/9ecf779972d90ba49c06d968637d720dd632c55bbf19d441fb42bf17a411e794/small.pt''',
    '''medium.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d7440d1dc186f76616474e0ff0b3b6b879abc9d1a4926b7adfa41db2d497ab4f/medium.en.pt''',
    '''medium''': '''https://openaipublic.azureedge.net/main/whisper/models/345ae4da62f9b3d59415adc60127b97c714f32e89e936602e85993674d08dcb1/medium.pt''',
    '''large''': '''https://openaipublic.azureedge.net/main/whisper/models/e4b87e7e0bf463eb8e6956e646f1e277e901512310def2c24bf0e11bd3c28e9a/large.pt''',
    '''large-v2''': '''https://openaipublic.azureedge.net/main/whisper/models/81f7c96c852ee8fc832187b0132e569d6c3065a3252ed18e56effd0b6a73e524/large-v2.pt''',
}






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	lowercase       =    ['layers', 'blocks']
	for k in ignore_keys:
		state_dict.pop(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)


UpperCAmelCase	      = {
    '''blocks''': '''layers''',
    '''mlp.0''': '''fc1''',
    '''mlp.2''': '''fc2''',
    '''mlp_ln''': '''final_layer_norm''',
    '''.attn.query''': '''.self_attn.q_proj''',
    '''.attn.key''': '''.self_attn.k_proj''',
    '''.attn.value''': '''.self_attn.v_proj''',
    '''.attn_ln''': '''.self_attn_layer_norm''',
    '''.attn.out''': '''.self_attn.out_proj''',
    '''.cross_attn.query''': '''.encoder_attn.q_proj''',
    '''.cross_attn.key''': '''.encoder_attn.k_proj''',
    '''.cross_attn.value''': '''.encoder_attn.v_proj''',
    '''.cross_attn_ln''': '''.encoder_attn_layer_norm''',
    '''.cross_attn.out''': '''.encoder_attn.out_proj''',
    '''decoder.ln.''': '''decoder.layer_norm.''',
    '''encoder.ln.''': '''encoder.layer_norm.''',
    '''token_embedding''': '''embed_tokens''',
    '''encoder.positional_embedding''': '''encoder.embed_positions.weight''',
    '''decoder.positional_embedding''': '''decoder.embed_positions.weight''',
    '''ln_post''': '''layer_norm''',
}






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	lowercase       =    list(s_dict.keys()							)
	for key in keys:
		lowercase       =    key
		for k, v in WHISPER_MAPPING.items():
			if k in key:
				lowercase       =    new_key.replace(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)

		print(F'''{key} -> {new_key}'''							)

		lowercase       =    s_dict.pop(__SCREAMING_SNAKE_CASE							)
	return s_dict






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	lowercase  ,					lowercase       =    emb.weight.shape
	lowercase       =    nn.Linear(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							bias=__SCREAMING_SNAKE_CASE							)
	lowercase       =    emb.weight.data
	return lin_layer






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	os.makedirs(__SCREAMING_SNAKE_CASE ,							exist_ok=__SCREAMING_SNAKE_CASE							)
	lowercase       =    os.path.basename(__SCREAMING_SNAKE_CASE							)

	lowercase       =    url.split('/'							)[-2]
	lowercase       =    os.path.join(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							)

	if os.path.exists(__SCREAMING_SNAKE_CASE							) and not os.path.isfile(__SCREAMING_SNAKE_CASE							):
		raise RuntimeError(F'''{download_target} exists and is not a regular file'''							)

	if os.path.isfile(__SCREAMING_SNAKE_CASE							):
		lowercase       =    open(__SCREAMING_SNAKE_CASE ,							'rb'							).read()
		if hashlib.shaaaa(__SCREAMING_SNAKE_CASE							).hexdigest() == expected_shaaaa:
			return model_bytes
		else:
			warnings.warn(F'''{download_target} exists, but the SHA256 checksum does not match; re-downloading the file'''							)

	with urllib.request.urlopen(__SCREAMING_SNAKE_CASE							) as source, open(__SCREAMING_SNAKE_CASE ,							'wb'							) as output:
		with tqdm(
		    total=int(source.info().get('Content-Length'							)							) ,							ncols=80 ,							unit='iB' ,							unit_scale=__SCREAMING_SNAKE_CASE ,							unit_divisor=1024							) as loop:
			while True:
				lowercase       =    source.read(8192							)
				if not buffer:
					break

				output.write(__SCREAMING_SNAKE_CASE							)
				loop.update(len(__SCREAMING_SNAKE_CASE							)							)

	lowercase       =    open(__SCREAMING_SNAKE_CASE ,							'rb'							).read()
	if hashlib.shaaaa(__SCREAMING_SNAKE_CASE							).hexdigest() != expected_shaaaa:
		raise RuntimeError(
		    'Model has been downloaded but the SHA256 checksum does not not match. Please retry loading the model.'							)

	return model_bytes






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	if ".pt" not in checkpoint_path:
		lowercase       =    _download(_MODELS[checkpoint_path]							)
	else:
		lowercase       =    torch.load(__SCREAMING_SNAKE_CASE ,							map_location='cpu'							)
	lowercase       =    original_checkpoint['dims']
	lowercase       =    original_checkpoint['model_state_dict']
	lowercase       =    state_dict['decoder.token_embedding.weight']
	remove_ignore_keys_(__SCREAMING_SNAKE_CASE							)
	rename_keys(__SCREAMING_SNAKE_CASE							)
	lowercase       =    True
	lowercase       =    state_dict['decoder.layers.0.fc1.weight'].shape[0]

	lowercase       =    WhisperConfig(
	    vocab_size=dimensions['n_vocab'] ,							encoder_ffn_dim=__SCREAMING_SNAKE_CASE ,							decoder_ffn_dim=__SCREAMING_SNAKE_CASE ,							num_mel_bins=dimensions['n_mels'] ,							d_model=dimensions['n_audio_state'] ,							max_target_positions=dimensions['n_text_ctx'] ,							encoder_layers=dimensions['n_audio_layer'] ,							encoder_attention_heads=dimensions['n_audio_head'] ,							decoder_layers=dimensions['n_text_layer'] ,							decoder_attention_heads=dimensions['n_text_state'] ,							max_source_positions=dimensions['n_audio_ctx'] ,							)

	lowercase       =    WhisperForConditionalGeneration(__SCREAMING_SNAKE_CASE							)
	lowercase  ,					lowercase       =    model.model.load_state_dict(__SCREAMING_SNAKE_CASE ,							strict=__SCREAMING_SNAKE_CASE							)
	if len(__SCREAMING_SNAKE_CASE							) > 0 and not set(__SCREAMING_SNAKE_CASE							) <= {
	    "encoder.embed_positions.weights",
	    "decoder.embed_positions.weights",
	}:
		raise ValueError(
		    'Only `encoder.embed_positions.weights` and `decoder.embed_positions.weights`  are allowed to be missing,'
		    F''' but all the following weights are missing {missing}'''							)

	if tie_embeds:
		lowercase       =    make_linear_from_emb(model.model.decoder.embed_tokens							)
	else:
		lowercase       =    proj_out_weights

	model.save_pretrained(__SCREAMING_SNAKE_CASE							)


if __name__ == "__main__":
	UpperCAmelCase	      = argparse.ArgumentParser()
	# # Required parameters
	parser.add_argument('''--checkpoint_path''', type=str, help='''Patht to the downloaded checkpoints''')
	parser.add_argument('''--pytorch_dump_folder_path''', default=None, type=str, help='''Path to the output PyTorch model.''')
	UpperCAmelCase	      = parser.parse_args()

	convert_openai_whisper_to_tfms(args.checkpoint_path, args.pytorch_dump_folder_path)



def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	if not isinstance(__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
		raise TypeError('Input value must be an \'int\' type'							)

	lowercase       =    0
	while number:
		position += 1
		number >>= 1

	return position


if __name__ == "__main__":
	import doctest

	doctest.testmod()

