kromskii2/alltalk_tts
1
0 Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Fix Dataset Validation when no errors found

Browse Source 
Fixes an issue where the dataframe errors if no transcription errors found.
Added debugging option for dataset validation
This commit is contained in:
erew123 authored and GitHub committed 2024-11-16 15:49:41 +00:00
1 parent f938f83131
commit 80dd102da8
1 file changed
+55 -11
Download Patch File Download Diff File Expand all files Collapse all files
finetune.py
+55 -11
View File
@@ -255,6 +255,7 @@ class DebugLevels:
AUDIO = False # Audio processing statistics and info AUDIO = False # Audio processing statistics and info
SEGMENTS = False # Detailed segment information SEGMENTS = False # Detailed segment information
DUPLICATES = False # Duplicate handling information DUPLICATES = False # Duplicate handling information
VALIDATION = False # DataSet validation handling
def debug_print( def debug_print(
@@ -286,6 +287,8 @@ def debug_print(
print(f"{prefix} [SEG] {message}") print(f"{prefix} [SEG] {message}")
elif level == "DUPLICATES" and DebugLevels.DUPLICATES: elif level == "DUPLICATES" and DebugLevels.DUPLICATES:
print(f"{prefix} [DUP] {message}") print(f"{prefix} [DUP] {message}")
elif level == "VALIDATION" and DebugLevels.VALIDATION:
print(f"{prefix} [VAL] {message}")
class AudioStats: class AudioStats:
@@ -1968,13 +1971,17 @@ def load_and_display_mismatches():
# Load and combine metadata from CSV files # Load and combine metadata from CSV files
metadata_dfs = [] metadata_dfs = []
for csv_path in vat_csv_paths: for csv_path in vat_csv_paths:
debug_print(f"Reading CSV file: {csv_path}", "VALIDATION", is_info=True)
metadata_df = pd.read_csv(csv_path, sep="|") metadata_df = pd.read_csv(csv_path, sep="|")
debug_print(f"CSV columns: {metadata_df.columns.tolist()}", "VALIDATION", is_info=True)
debug_print(f"Number of rows: {len(metadata_df)}", "VALIDATION", is_info=True)
# Add source CSV tracking # Add source CSV tracking
metadata_df["source_csv"] = csv_path metadata_df["source_csv"] = csv_path
metadata_df["row_index"] = metadata_df.index metadata_df["row_index"] = metadata_df.index
metadata_dfs.append(metadata_df) metadata_dfs.append(metadata_df)
metadata_df = pd.concat(metadata_dfs, ignore_index=True) metadata_df = pd.concat(metadata_dfs, ignore_index=True)
debug_print(f"Total combined rows: {len(metadata_df)}", "VALIDATION", is_info=True)
# Load Whisper model # Load Whisper model
device = "cuda" if torch.cuda.is_available() else "cpu" device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -1991,6 +1998,8 @@ def load_and_display_mismatches():
), total=total_files, unit="file", disable=False, leave=True): ), total=total_files, unit="file", disable=False, leave=True):
audio_file = row["audio_file"] audio_file = row["audio_file"]
expected_text = row["text"] expected_text = row["text"]
debug_print(f"Processing file {index + 1}/{total_files}: {audio_file}", "VALIDATION", is_info=True)
debug_print(f"Expected text length: {len(expected_text)}", "VALIDATION", is_info=True)
audio_file_name = audio_file.replace("wavs/", "") audio_file_name = audio_file.replace("wavs/", "")
audio_path = os.path.normpath( audio_path = os.path.normpath(
os.path.join( os.path.join(
@@ -1999,6 +2008,7 @@ def load_and_display_mismatches():
if not os.path.exists(audio_path): if not os.path.exists(audio_path):
missing_files.append(audio_file_name) missing_files.append(audio_file_name)
debug_print(f"File not found: {audio_path}", "GENERAL", is_warning=True)
if vat_progress is not None: if vat_progress is not None:
vat_progress((index + 1, total_files), vat_progress((index + 1, total_files),
desc="Processing files") desc="Processing files")
@@ -2013,26 +2023,40 @@ def load_and_display_mismatches():
# Get the full transcription from the result # Get the full transcription from the result
transcribed_text = result["text"].strip() transcribed_text = result["text"].strip()
debug_print(f"Transcribed text length: {len(transcribed_text)}", "VALIDATION", is_info=True)
# Normalize and compare texts # Normalize and compare texts
normalized_expected_text = normalize_text(expected_text) normalized_expected_text = normalize_text(expected_text)
normalized_transcribed_text = normalize_text(transcribed_text) normalized_transcribed_text = normalize_text(transcribed_text)
debug_print(f"Normalized expected text length: {len(normalized_expected_text)}", "VALIDATION", is_info=True)
debug_print(f"Normalized transcribed text length: {len(normalized_transcribed_text)}", "VALIDATION", is_info=True)
if normalized_transcribed_text != normalized_expected_text: if normalized_transcribed_text != normalized_expected_text:
mismatches.append( debug_print("Mismatch found! Adding to mismatches list", "VALIDATION", is_info=True)
{ mismatch_entry = {
"expected_text": row["text"], "expected_text": row["text"],
"transcribed_text": transcribed_text, "transcribed_text": transcribed_text,
"filename": audio_file_name, "filename": audio_file_name,
"full_path": audio_path, "full_path": audio_path,
"row_index": row["row_index"], "row_index": row["row_index"],
"source_csv": row["source_csv"], "source_csv": row["source_csv"],
} }
) debug_print(f"Mismatch entry keys: {mismatch_entry.keys()}", "VALIDATION", is_info=True)
mismatches.append(mismatch_entry)
if vat_progress is not None: if vat_progress is not None:
vat_progress((index + 1, total_files), desc="Processing files") vat_progress((index + 1, total_files), desc="Processing files")
debug_print(f"Total mismatches found: {len(mismatches)}", "GENERAL", is_info=True)
if mismatches:
debug_print("Sample mismatch entry:", "VALIDATION", is_info=True)
debug_print(str(mismatches[0]), "VALIDATION", is_info=True)
if missing_files:
debug_print("Missing files:", "GENERAL", is_warning=True)
for file_name in missing_files:
debug_print(f"- {file_name}", "GENERAL", is_warning=True)
if missing_files: if missing_files:
debug_print("", "GENERAL") debug_print("", "GENERAL")
debug_print( debug_print(
@@ -2059,6 +2083,14 @@ def load_and_display_mismatches():
vat_progress, vat_progress,
) )
if not mismatches:
debug_print("No transcription mismatches found!", "GENERAL", is_info=True)
empty_df = pd.DataFrame(columns=["expected_text", "transcribed_text", "filename",
"full_path", "row_index", "source_csv"])
display_df = pd.DataFrame(columns=["expected_text", "transcribed_text", "filename"])
display_df.loc[0] = ["No bad transcriptions", "No bad transcriptions", "N/A"]
return empty_df, display_df, "No transcription mismatches found - all transcriptions match!"
# Convert mismatches list to DataFrame # Convert mismatches list to DataFrame
df = pd.DataFrame(mismatches) df = pd.DataFrame(mismatches)
@@ -3486,10 +3518,11 @@ if __name__ == "__main__":
with gr.Accordion("🔍 Dataset Creation Debug Settings", open=False): with gr.Accordion("🔍 Dataset Creation Debug Settings", open=False):
def update_debug_levels( def update_debug_levels(
gpu, model, data, general, audio, segments, duplicates): gpu, model, data, validation, general, audio, segments, duplicates):
DebugLevels.GPU_MEMORY = gpu DebugLevels.GPU_MEMORY = gpu
DebugLevels.MODEL_OPS = model DebugLevels.MODEL_OPS = model
DebugLevels.DATA_PROCESS = data DebugLevels.DATA_PROCESS = data
DebugLevels.VALIDATION = validation
DebugLevels.GENERAL = general DebugLevels.GENERAL = general
DebugLevels.AUDIO = audio DebugLevels.AUDIO = audio
DebugLevels.SEGMENTS = segments DebugLevels.SEGMENTS = segments
@@ -3501,6 +3534,7 @@ if __name__ == "__main__":
debug_gpu: True, debug_gpu: True,
debug_model: True, debug_model: True,
debug_data: True, debug_data: True,
debug_validation: True,
debug_general: True, debug_general: True,
debug_audio: True, debug_audio: True,
debug_segments: True, debug_segments: True,
@@ -3512,6 +3546,7 @@ if __name__ == "__main__":
debug_gpu: False, debug_gpu: False,
debug_model: False, debug_model: False,
debug_data: False, debug_data: False,
debug_validation: False,
debug_general: False, debug_general: False,
debug_audio: False, debug_audio: False,
debug_segments: False, debug_segments: False,
@@ -3543,6 +3578,11 @@ if __name__ == "__main__":
value=DebugLevels.DATA_PROCESS, value=DebugLevels.DATA_PROCESS,
info="Data processing, words, sentences", info="Data processing, words, sentences",
) )
debug_validation = gr.Checkbox(
label="Dataset Validation",
value=DebugLevels.VALIDATION,
info="Dataset Validation, amount, sentences, files",
)
with gr.Column(scale=1): with gr.Column(scale=1):
debug_general = gr.Checkbox( debug_general = gr.Checkbox(
@@ -3575,6 +3615,7 @@ if __name__ == "__main__":
debug_gpu, debug_gpu,
debug_model, debug_model,
debug_data, debug_data,
debug_validation,
debug_general, debug_general,
debug_audio, debug_audio,
debug_segments, debug_segments,
@@ -3586,6 +3627,7 @@ if __name__ == "__main__":
debug_gpu, debug_gpu,
debug_model, debug_model,
debug_data, debug_data,
debug_validation,
debug_general, debug_general,
debug_audio, debug_audio,
debug_segments, debug_segments,
@@ -3602,6 +3644,7 @@ if __name__ == "__main__":
debug_gpu, debug_gpu,
debug_model, debug_model,
debug_data, debug_data,
debug_validation,
debug_general, debug_general,
debug_audio, debug_audio,
debug_segments, debug_segments,
@@ -3616,6 +3659,7 @@ if __name__ == "__main__":
debug_gpu, debug_gpu,
debug_model, debug_model,
debug_data, debug_data,
debug_validation,
debug_general, debug_general,
debug_audio, debug_audio,
debug_segments, debug_segments,