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| parts = line.strip().split(split) | ||
| if has_speakers: | ||
| #need to add option for all conditions | ||
| if has_speakers or has_conditions: #this might be wrong @Johannah |
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True or True = True
is this to say, the last item is either the speaker, or the condition?
given they're both booleans you could do:
has_speakers is not has_conditions
or put has_speakers and has_conditions first, so that this case is already handled and therefore excluded from has_speakers or has_conditions
| if len(self.audiopaths_and_text[0]) < expected_columns: | ||
| raise ValueError(f'Expected {expected_columns} columns in audiopaths file. ' | ||
| 'The format is <mel_or_wav>|[<pitch>|]<text>[|<speaker_id>]') | ||
| 'The format is <mel_or_wav>|[<pitch>|]<text>[|<speaker_id>|<condition_id>]') |
| symbol_set='english_basic', | ||
| p_arpabet=1.0, | ||
| n_speakers=1, | ||
| n_conditions=1, |
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default is 1 but to have conditions there should be more than 1? If 1 is a way of saying there are no conditions, why not 0?:
| def __getitem__(self, index): | ||
| # Separate filename and text | ||
| if self.n_speakers > 1: | ||
| if self.n_speakers > 1 and self.n_conditions < 1: |
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this block is a little cumbersome but I really appreciate how legible it is appreciation comment
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| if self.n_speakers > 1: | ||
| #specifying the fields | ||
| if self.n_speakers > 1 and self.n_conditions < 1: |
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what? my brain is tired and can't exactly figure out what's going on here
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| audiopaths = [batch[i][7] for i in ids_sorted_decreasing] | ||
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| if batch[0][8] is not None: |
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I imagine this is the bit that would need updating once the other code is merged?
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| (inputs, input_lens, mel_tgt, mel_lens, pitch_dense, energy_dense, | ||
| speaker, attn_prior, audiopaths) = inputs | ||
| speaker, attn_prior, audiopaths, condition) = inputs |
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as a side-note I am wondring if we should make inputs/outputs some enum or datatype that also doesn't rely on indices to get different things out
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| # Predict pitch | ||
| pitch_pred = self.pitch_predictor(enc_out, enc_mask).permute(0, 2, 1) | ||
| pitch_pred = self.pitch_predictor(enc_out, enc_mask).permute(0, 2, 1) #maybe we want to condition pitch prediction on the conditioning parameter. |
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cool idea, we should make a ticket for this
| ) | ||
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| def forward(self, dec_inp, seq_lens=None, conditioning=0): | ||
| def forward(self, dec_inp, seq_lens=None, conditioning=0, conditioning_2=0): #here when called we add speaker or other discrete condition |
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you could make condition a tuple, or rename the conditionings to conditioning_speaker conditioning_other
| prepare_tmp(args.pitch_online_dir) | ||
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| trainset = TTSDataset(audiopaths_and_text=args.training_files, **vars(args)) | ||
| trainset = TTSDataset(audiopaths_and_text=args.training_files, **vars(args)) #making changes here ./fastpitch/data_function.py |
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I think this comment can be deleted?
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| gen_kw = {'pace': args.pace, | ||
| 'speaker': args.speaker, | ||
| 'condition': args.condition, #@Johannah have to add condition here |
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I think this comment can be deleted?
| def infer(self, inputs, pace=1.0, dur_tgt=None, pitch_tgt=None, | ||
| energy_tgt=None, pitch_transform=None, max_duration=75, | ||
| speaker=0): | ||
| speaker=0, condition=0): |
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so because this is the condition index, the default is 0 (despite no condition being n_conditions = 1 and so far there only being able to be 1 condition?)
Just making sure I understand, once again my brain is melting
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@johannahom my apologies for making all of these separarately, but mostly tomorrow I need to train a model from this branch to see how it goes |
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Still need to fix single conditions